experiment_data_similarity.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da148ae1",
   "metadata": {},
   "source": [
    "# Measure of Contribution to Model Performance and Deletion Robustness\n",
    "\n",
    "## Data Similarity\n",
    "\n",
    "How does DeRDaVa view data sources with similar data? Sample experiments are given below:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1681c8f6",
   "metadata": {},
   "source": [
    "### Synthetic Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "14dcf237",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qgpaF4zQicEBmflvXhFA82CXWYgkRRwMteYg9Q53uoK8Dx1Wp5GU4hKqAhIQE2edvvPFGo8dZWVlo1aqV9HjBggU4fPgwNm7ciIkTJ2Ly5MlQq9XS6tOePXvi3XffdVm7yTc5OiRqbecFS0yL3DYOC0CfNdkW39PeOnA7c6ogALLbaBl6PaMQr2cUWjlC5/EdF1Bep3Vo+NPWVmLkQXJDjs4MQ5quBFWqKDCRF2GA86DAwECsX78eK1aswKpVq3DkyBFoNBpcf/31GD9+PGbOnImgoCDn36Aep5L3cqYEhqWdFywxLXL7UOcYq71WWSW1eLZHHF7Zn2+zbIj+5bcGJuJcWR0W77NvWy05WtjeOsuUM4GWFKIPUN5QB840GFYVeK4tRAA0UCNfiLP7eAY4BYii8+XnVSoVpk6diqlTpyrYoitaQPfbKU8Eqm0eTT7C2R4kuZ0XAPkN4k17+D44XGRWe00tAH/kVeGeH85LQe+2luHYlF1udyCbem0jjGwdic+OF+P1Q7Z73G5IDMEek2FTZ+q3ORpoyUfY2gfV2hZdRvfNF5XZjQsXyEEaqFEoNEKRGI0Ssczu8xjg/F24CIQDKGeQ8xdK9iDJbSfVPDLQfBUqdKtQV2YWSe/5TI84aXN5QBf0NmaX2/3e+hpySeGBGN8+Gm8cKrQZ/PZdrJINks4Mf1oKtOQG3h5y1t16dYECa8GRi2igRgEaoRjR0IqOL0lggGsopCAHIB+A+dxv8iFK9CBZmku37vZmsj18D3SOwQOdY6T3tHfhghzTGnJJ4YFY3LcxZqVfkkKc3Dw5uSApF15NexXJgzwd1vSLEGwJCNWFNgY2crE6UY1CVRyKtFEQBefXkjLANTThV24VV3rkGOR8Vn17kCzNpauoE6328Bm+pzMb2MvVkMstr0XzyEB8M6IZzpbWQRBENIsIxOgN52wGSdN/A25S7wesDXV6E0+HU/IpUnBDtG4EwpmCmQYY4BqqMFE3R45BrsGyNpfuxqQwaT9UrShY3M3ANOjd2jJcdhhVJQDP9rhaoNdSAWDTwGVvkNRzdIUu+Qlbc9+U4AuBkrxSHQJ0Q6VCtNn2g/XBANfQ6YNcpaAbWq1wfkEG+RZbc+l2nq+w2ZMlt4G9aYCb0kXXY6a/rr4AccqVeWvWApejQ8XcpJ4UJberA5Gd6hCAAiEOxWIUxPp2t8lggCOdUBFoBga5BsZSQLLVk2U6x8xw9aoh1ZUhT/11TXvbHrRSnsS0py3rSskSa0GMNd78nCNDq2N+NC/Ca6t8ieHrdZXsaSOn1CEA+YhDCaIU7XEzxQBHxoyCnAiY72FOfkZuLp21nixLPXOW9lDVh7Hc8lqjRQpaEViZWWS2WME0cDkyp4013vyQYWAzfZ7DmeRFasUAFKjiUSJGuqTHzRQDHMnTB7mqKz1y5eyRa0gs9WSFBQhGm8sb9sylRAVaLfHxzK6L5qtKReurSp2Z08Yab2Rxj1IuOiAXqEUgCoQ4lCDSpT1uphjgyLoQEWgKBrkGxlJP1vdZZWZ7k+p75s6U1hoFNAFXw1jG5UrsyjEfvtIPsVpaVersnDbWeCOnWCrsSySjFoG6oVIxEvVeUuoEBjiyjxTkABQIQBmDnL8z7ckCgFnpl8yOU+l75nZfMgtw/ZqGAQD2ymw6DwDDWkVYXVXKOW3kNPa2kYvUiIG6oVJtBCDUvxyIs5yvIEcNUwiA5CsrVyM89F1LbpMUrispkhSuK9wrF9sf6hyD8jpRdvcG/V6pvWTKkADA5C4xFt9bv1Di2R5xUF/5VuOctgZCH74sDYXaUlcJrO6pu3nDvqvkF2oQhAtCErLRStfrJnj2dyB74Mg5+iDHHrkGQ643TAXdEChgXtTXsKesa0Io7rwmEmtPlkqv33lNJLomyA9TmS5csFRDjgiAcrsoWFqFyt68Bq0GQcgX4lEqRuhWXHlJ3wV74Kh+pB45EYj0ku9qcomk8EA82yNO+qGhFq7uqKCfM2etp+zVfk3w7YhmeL5XPL4d0Qyv9msi+z5yCxde2Z/P8EaW+crODeRTqsUg5ArJyEYrXXjzMuyBI2WECECSCDSCrkeulD1y/uaLE8W6zeuh+wP0mR5xRuU87Fn92TUh1GKvmx6L8ZJFrt6vlIsYCEA1glEgxKEUEeYbMnsRBjhSVjCuBrlCASjx4u9+sptpr5gIXa/YyNaRRqFKidWfXLhAVnE4k1ykGsHIF+JRJoZ7dXDT4xAquUYwgCYi0FIEoji06uus9YopzZ7hWCKfwkUVXq0awcgRmuI0WurCm4/wWA9cVVUVfvrpJ5w4cQJqtRqdO3fGwIEDoVarbZ6bk5ODuXPnQhAErFy50g2tJacFC7ogpx9aZY+cT3J3rxiL8RKRq1UhBPmIQzl8o8fNlEcC3JdffolHH30UeXl5Rs83bdoUixcvxoQJE6yeX1hYiFWrVjHA+ZIgXA1yhQJQ7IP/tzRgntiiisV4icgVqhCCfCEe5WKYp5tSL24PcJ9++inuv/9+iKIIUTT+JX7u3Dncd9992LhxI1asWIHQUE4i9TtBABJFIBZXgpx+Sjx5O/aKkc/gPDmSYRTc/KAPwa0B7tKlS5g+fTq0Wt1mPKNGjUJaWhpqamqwfft2bNq0CRqNBp999hmysrKwadMmREVFubOJ5C76INdIAApwpUeOQc7bsVeM/BqDn1+qFMKQjzhUiKF+Edz03BrgVq5ciZKSEqhUKnz66acYN26c9NoTTzyB/fv345///CeOHDmC3377DWlpadi8eTNiY2Pd2Uxyp0AAidAFOf3Qqh/9D0ZEbsDgRTKMgpsfcusq1M2bN0MQBNxzzz1G4U2vR48e2LNnD0aMGAFRFHHw4EGkpaWhoKDAnc0kTwgE0FgEWgGI8dzeckRE5NsqEIazaI6zYjO/DW+AmwPckSNHAAD/+Mc/LB4THh6Ob775Bg888ABEUURGRgbS0tKQn5/vrmaSJ0lBTgRiwCBH1JDpe9Ym7GNhXbKpQgjHWaEFzqEZKuH/3y9uHUItKioCADRv3tzqcfrVpUFBQXjvvffwxx9/YNCgQdi6dSvi4+Pd0FLyuEABaIyrq1aLOLTqL/Sb1KdwIQQ1FBzidakKIRz5iEOlGOLppriVWwNccHAw6urqUFpaavtgAO+88w7UajXefvttHD58GGlpadi2bZuLW0leJQBAgsGqVQY5n2a6Sf2iPo2NtuMiksW9TklGuRCBfLERqhpYcNNz6xBqs2bNAADHjx+3+5w333wT06dPhyiKOHz4MAYOHIjLly+7qonkrfRBLgW6BQ8cWvU5cpvUP7f7EnLLld/NgYj8V7kQgTNogfNiMqrQMMMb4OYAd91110EURYd70d544w08+uijEEURmZmZuPvuu13UQvJ6AQDiRSBFZJDzMe7cjouI/E8ZGNwMuTXA9eun6wJfv349KioqHDr39ddfx2OPPQZRFNkDR0CAoAtyraGbJydwXNXb6bfjMsRN6onIljIhEqfFFsgBg5shtwa42267DQBQXl6ODz/80OHzX3vtNcyYMcNsBwdqwNQA4gG0FoA4wc3f0eQIblJPRI4oEyJxGi2RIyahWmBwM+XWRQytW7fGxIkTcf78eezfv9+payxfvhxBQUFYs2aNwq0jn6YGEHel9EiRABSKgNbDbSIz3I6LiGwpFaJQIMaiWgz2dFO8miCyO8vvlJSUIDo6GsXFBxAVFeHp5niGBkCxABQwyBH5PK5CbRBKhSjka2NRIzTc4FZWVoLu3aNRXFxscytRt29mT+QWagCNRCBaBIpVDHJERF6qBFEoQCPUiEFcmOYARWcMPf/880pejqj+1IIuyLWGbq6c2tMNIiKHcUcGvyOKQIkQjWy0wgU0QQ2CPN0kn6NoD9zLL7+MwsJCvPnmm0pelqj+VNCtVo3B1aFVjWebRETU0IgiUKqKRr4Yi1qRoa0+FB9Cfeedd1BYWIj//e9/UKvZ3UFeRgUgVgSiwSBHROQm+h63AqERasVADpUqwCVz4D7//HMUFRVh7dq1CAnh0l/yQkZBDkABGOSIiBQmQtAFN8SiFlx1riRF58A1bdoUACCKIn744QcMGTIEJSUl9bpmVlYWd14g11FBt89qigg0FjhHjohIASIEFAsxyBJb4aLYmOHNBRQNcL/88gvatWsnPd69ezf69++PS5cuOXytgoICzJw5Ex07dsSXX36pZDOJzKkEIObKYofGAtdnExE5QYSAIlwNbnUCg5urKBrgmjdvjvT0dPTo0UPaLSEjIwM333wzTp8+bdc1qqursXjxYrRp0wZvvPEGampqlGwikXUCdEEuBUAigxwRkT1ECCgSYpGFFFwCg5s7KL7xUFxcHLZv3460tDSIoghBEPDXX3+hb9++OHLkiNVzV61ahbZt22LOnDkoLi5WumlE9hOgqyHHIEdEZJEIAYW4EtzEBNTxh6XbuGTnyPDwcGzcuBF33XWXFOLOnz+Pfv36Ye/evWbH//DDD+jatSsefPBBnDt3TjpHFEWoVCrcf//9rmgmkW1GQQ4MckREuBLchEb4W0zBZTC4eYLLtv4ODAzEF198galTp0qBrKCgAIMHD8bWrVsBAL///jtuueUWDB8+HIcPH5aOA3QLIUaPHo0///zTqY3viRQlQLdiNQVAEwGcj0tEDZFWNAhuYjw0AoObp7j0X14QBLzzzjtISEjAggULIAgCysrKcPvtt2Pw4MHYtGkTRFE0C25paWlYuHAhevbs6crmETlOABAlApEASgUgXwRqPd0oIiLX0oq6OW6FQiw0opp13LyAW6Lz/PnzkZCQgJkzZ0IQBFRXV2Pjxo3SQgdAF9x69eqFhQsXYtCgQe5oFpHzDINcmQDkMcgRkf/RQqULboiBhnWWvIpbApxWq0VISAiio6NRXFwszW/T97p17NgRCxYswKhRo9zRHCLlCAAiRSBCBMpUuh45LpwmIh8nBTcxRtfjRl7H5QFuzZo1eOGFF/DXX38ZPa8PcWq1Gq+++ipuvfVWVzeFyHUEgUGOiHyeFioUCo1QqI2Glj1uXs1lixg2bdqE7t27Y/z48Thx4oQ0XCqKIgICAqQeOI1GgzvuuIPFesk/6INcKwDJAsC9monIB2hEFfKFePwtpiBfbAStwPDm7RQPcLt370a/fv1w++2349ChQ0ZDpQBw77334uTJk/j3v/8NQNcTV1NTgwkTJuDdd99Vujleb9WqVRAEweotIiLC080kZ0QYBjnR1tFERG6ngRp5iEeW0JrBzccoOoQ6fPhw/PDDDwBgtrJ08ODBWLp0Kbp27QoAmDlzJho1aoSHHnoIGo0GGo0G06dPR15eHubOnatks3xCYGAgGjVqJPtaeHi4m1tDiooQgQgBKAOQD6Da0w0iooZOAzUKhUYoEqOhdd1gHLmQogFu06ZNUmjTz3Hr2rUrlixZgiFDhpgdP3HiRMTExODuu+9GdXU1RFHEiy++iMuXL+O1115Tsmle76abbsKOHTs83QxypYgrt/Irq1YZ5IjIzYyCm8jg5stc8tUTRRHNmjXDqlWrcPDgQdnwpjdy5Ehs2rQJkZGRUuh78803ce+990Kj0biieUSeFS4CLQE0FYBgTzeGiBoCDdS4LDTG32IKCsRY9rr5AcW/glFRUVi8eDFOnDiBiRMnGs1/s6R///7Ytm0b4uPjpRD32WefYeTIkaisrFS6iUTeQR/kmglAiKcbQ0T+qE68GtwKxRiIAoObv1D0K/nEE0/g1KlTeOaZZxAc7FjXQrdu3bBr1y40a9ZMCnE//PADBg8ejKKiIiWbSeRdwkSgBRjkiEgxdQjAZaExsoTWDG5+StGv6KuvvmpxIr492rVrh927d6N9+/bSc7/++ituvvlmJZrn1TIzM9G5c2eEhoYiMjISXbp0wRNPPIGsrCxPN43cRQpyAEI93Rgi8kV1CMAlIRFZuNLjxj2v/JbXRfJmzZohPT0dPXr0kGrHHTlyxMOtcr28vDwcPXoUYWFhqKqqQmZmJv7zn/+gc+fOWL16tdVzq6urUVJSYnQjHxYGoDmA5gIQxh++RGSbYXArEqMZ3BoArwtwANCoUSNs3769QeyJmpycjJdeegmHDx9GVVUV8vPzUVZWhu+//x6dOnVCZWUl7r//fuzcudPiNRYtWoTo6Gjp1rx5czd+AnKZUBFoJjLIEZFFtWIALoLBrSESRMMd5b1MTU0N7r77bnz77bcNckVqcXExevTogZMnT+LGG2/EL7/8IntcdXU1qquv1qQoKSlB8+bNUVx8AFFRLALsNyoBFAhAudf+L0tEblKLQBQIcSgRIxna/EhZWQm6d9ftGx8VFWX1WK/sgdMLCgrCV199hUmTJnm6KR4RHR2N5557DgDw22+/IS8vT/a44OBgREVFGd3ID4UCaCoCLQQgnD+wiRqiWgTiotAE2WiFYjGK4a0Bc/lm9vWlUqmwYsUKTzfDY2644QYAutp6WVlZiI+P93CLyONCRKApgCpBt7MDe+SI/F6NGIgCVTxKtBEAQxvBBwIcEVkgBTnohlbLGOSI/E0Ngq4MlUYAosDsRhIGOC+3Z88e6X6rVq081xDyXiEAkkUGOSI/UoMg5CMOpeKVHjcGNzLBAOdBoiha3amipKQEixcvBgD06tULCQkJ7moa+SKjIAegzMPtISKH1SAI+UL8leAGBjeyyKsXMfi706dPo3fv3li5ciXOnDkjPV9TU4MffvgBffr0wYkTJ6BSqbBo0SIPtpR8SgiAZOi26YrkT38iX1AtBiFXSEY2Wl0Nb0RWsAfOw/bs2SMNk4aEhCA8PBwlJSWora0FAISFheHdd99tEDXxSGHBAJJEoBF0Q6ulHFol8jbVCEY+4lAmRAD8X5QcwADnQYmJiXj99deRnp6OjIwMXL58GcXFxQgPD0fbtm2RlpaGRx55BC1btvR0U8mXGQa5QgEo4W8JIk+rRjDyhXiUieGebgr5KK8u5EvOKSkpQXR0NAv5krwa6HrkGOSI3K5K1AW3cjC4kTlHCvmyB46ooQkC0EQ/tAqAW+cSuVwVQq4EtzBPN4X8BAMcUUMVBKAJrg6tFrNHjkhpUnATwzjHjRTFAEfU0AUBSBSBWBEoVAHFWrB2AVH9VCIU+YhDBRjcyDUY4IhIJ0jQBblGgq5HrohBjshRlUKYLriJoZ5uCvk5BjgiMhYIoLEIxApXh1bZg0BkVQXCUCAwuJH7MMARkTwpyOmHVhnkiExVCOHIFxuhEqH8/4Pcym0BrqCgAEePHkVBQQGKi4uh1Wpx6623IjEx0V1NICJnBAq6IKdf7FDEIEdUIYQjH3GoFEM83RRqoFwa4C5duoQ333wTa9euxbFjx8xe37Jli2yA++ijj3D27FkAQHJyMh566CFXNpOI7BEAIEEEYsEgRw1WOXTBrYrBjTzMZQFu6dKleOGFF1BTUwO5WsHWNnEvKyvDvHnzIAgC1Go1RowYwZ46Im9hGOSKBKCQQY78X7kQgXyxEarA4EbeQfHN7DUaDcaMGYNZs2ahurra7HVrwU3vwQcfRFRUFERRhEajwerVq5VuJhHVVwCAeBFIgW7lKheskh8qFyJwBi1wXkxmeCOvoniAmz59Or755huIoghBECCKIlJTU/Hss8/irbfeku2NMxUWFoYRI0ZIjzdu3Kh0M4lIKfog1xpXghy748j3lSECp0UGN/Jeig6hpqen4/3335d62eLj47Fq1SoMHTpUOmb69Ol29cKNGjUKn376KURRxO7du1FTU4OgoCAlm0tESlJDF+RihatDq1pPN4rIMWVCJPLFRqhGMHuVyaspGuBeeOEFAIAoioiKisLPP/+MDh06OHWtG264QbpfXV2N48eP49prr1WknUTkQmoAcSIQAwY58hmliEQBGqFaDPZ0U4jsotgQamFhIXbt2gVBECAIAubOnet0eAOAZs2aITY2Vnost4qViLyYPsilAIgTXDBhg6j+SoUoZIstkYskXa8bkY9QrAcuPT0dGo0GAKBWqxUp/dG4cWMUFhYC0JUkISIfdCXIidFa1BUK0LJHjrxAmRCBIjEGdUIIBIE17cn3KPZdm5OTA0C3yrR169aIiYmp9zWjo6Ol+6WlpfW+HhG5n1YroqCgDmVlWtTV6VerCoCG5UfIvUQAWqhRhwCIqAJwAbp1daEICIiDWs3FCuQ7FAtwBQUF0v1GjRopck3DMiSBgYGKXJOI3EerFZGTU4OamgBERkYhLCwEarUaggDdb9NaAHVgkCOXEgHUIQB1CITWaCxfRG1tDUpLi1BZmQNBaA6Vir9ryDcoFuBc0VtmOGwaHx+vyDWJyH0KCupQUxOA5OREhITIrCIPwdUgVwsGOVKULrgFohaBAFSyv/CCgkIQGhqOixfPoqoqH8HBTdzcSiLnKDatOCEhAYBuBerp06eh1dZvksvZs2eRm5srPU5OTq7X9YjIvURRRFmZFpGREfLhTU8AEAQg7Mp/WbqB6kn3N0EgKhGGagSb9LqZU6nUCA+PBFBhV61SIm+gWIDr2rWrdL+iogK7d++u1/W+/PJL6b5arUbv3r3rdT0ixdVUAvN66m41lZ5ujdepqxNRVycgLMzOeUWGQS4YDHLkMEeDm6GgoFAIghaiWOe6BhIpSLEA165dO6SkpEhFev/97387fa2SkhIsX75cKknSs2dPREZGKtVUInIDfSe8Wq127EQBQCAY5Mhu+uBW4URw01Op9OdwiTT5BkUrM02cOBGiKEIURXz33Xf473//6/A1NBoNJk6ciPPnz0td2dOmTVOymUTkRnZsvGLhRDDIkVWmwU2s1680foORb1E0wD311FNo3LixtAfqQw89hKVLl0r14Ww5duwYBg0ahPXr10u9b+3atcOECROUbCYR+RIGOTKhbHAj8k2KVi8MDw/HBx98gNGjR0Or1UKj0WDWrFl4++23MX78eHTv3h0ApI3uDxw4gIKCApw8eRLbtm3Dtm3bpB48AAgNDcXq1avt2juViPycPsgFQFd6pAZctdrA6IJbEGoRwNBGDZ7i5advv/12vPXWW9Kwp35V6pIlS4yOE0URs2bNMntOH9YCAwPx0UcfITU1VekmEpEvY5BrcBjciMy55P+EKVOm4Mcff0RiYiIASKFMH9D0N31vm77HTf9cYmIitm7dirFjx7qieUTkD0yHVvl73e+IAGoQhAqEowZBDG9EBlz2f0NaWhqOHj2KhQsXIikpSQpppqFNTxRFxMTE4KWXXsLx48fRt29fVzWNiPyJPsiFgkHOhBAZCSEyEtmnT3u6KQ4RIZgEN06jITLl0h18o6OjMWvWLDzzzDPIyMjArl27cPToUeTn56OoqAhhYWGIj49HSkoKBg4ciF69eiEggJsKk4JqKoGF/XT3n9sJBIUqd+2gUGDePuWuR/VjOLSqgW5o1U8qQlRUVOC/q1dj448/IuPwYeTl50MQBDROSED366/HqNtvx5133IHQUAW/vz1AhIDaKzsn2BPaDh7cj9dfX4bdu3eisLAACQmNMWjQEPzrX7PQps01bmgxkecIIstO+52SkhJER0ejuPgAoqIiPN0cz3JlgCOrqqu1OHu2Ds2bJyM42MpODK4iwi+C3PqNGzHl8cdx4eJF6bnw8HCoVCqjbQuTk5Lw8YoVGNS/v/SccKV+Ztbhw2jVsqX7Gu0gR4MbAHz66X/x6KMPoa6uDoIgICoqCsXFxQB0/z5ffPEd+vcfZHcbamqqkZNzFgEBzaFSBTv1OYjqq6ysBN27R6O4uBhRUVFWj1VssEGj0aCkpES61dbWKnVpIiLHCdD1xoVBt+eqDw6trvrkE4waPx4XLl5E+7Zt8fGKFcjLzkbZhQsoyclB0blz+OqTTzDg5puRk5uLnfXcAcfdrg6Vhjk0VHr48B947LHJqKurw7hx9+DUqYs4d64ImZnZGDToFpSXl+Pee+/E5cuXXfwJiDxHsR9p//3vfxEbGyvddu3apdSliezDra3IEh8Mchl//omHZ86EVqvFsCFD8Pvu3bj37rsRFxcnHRMdHY0777gD2zduxOerViEywjd63J0NbnoLFryA2tpadOvWA++9919pL+4WLVri00/XoVmz5igqKsK//73YFc0n8gqK/Si7ePGitDghOjoagwbZ33VNROQWPhTk5s6fj+rqajRNTsbqDz+0Ob9t3J134l+PPWbXtTUaDTZt3oypjz+O7jffjMTWrRHUqBGS27bF6PHjse3nny2eq9VqseqTTzBw2DDEtWiBwNhYJLRqhc49e2LSI4/ghy1bzM7Jys7GIzNnot31qQhNSEB44wRc06ktbhs6EMuWLUJeXp5d7QaAoqIibN68EQDw6KP/MtuqLSIiApMmPQwA+Oqrz7g5PfktxVYMRFz5y08QBLT04rkWREQIgHEdOS+bI3c+Jwff//gjAODxhx9GdHS0XefZW/T86PHjGHbnndLjqKgoBAUFIffCBXyzYQO+2bABC198EbOfesrs3PsmT8bqNWukx9HR0SgpLUVefj6OHDuGI8eO4bZbbpFeP3joEAYMGybN1wsMDER4eDjOnj2Ds2fPID39Z3TtmopbbrnNrrb/+mu6NEVn0KAhsscMHnwr5s+fgwsXcnH8+FF06NDJrmsT+RLF/gZNSkpS6lJERO7hpT1yO3btknqORg4bpvj1gwIDMem++/DjN9+g+Px5FJ8/j7ILF3Dx77/xf88/D7VajTnz52PPPuNV1jvT07F6zRqo1WosX7xYmodXlZeHnL/+wqp330XfG2+Ujhch4F9znkdpaSl69LgB6ekHUVBQg7NnC3HxYjl+/nkfpk+fiago+wIqABw7dgQAkJjYxGg42ZBhYNMfT77pcnklDuXm4djlQhzKzcPlck6P0VOsB65jx44AdPXczp49q9RliYhcz7BHrha61asedPT4cQBAcHAw2rdrp/j127Vti5Vvv232fOOEBMx95hmIoogXFizAuytX4oaePaXXf7sS6G4ZNAgzp0+XnhcEAUlNmuD+e+4BAGghSDsn7N23BwDwyiuvoWvXqzvrhIWFoVu3HujWrYdDbb94MRcAkJSUbPGY0NBQxMTEoKioCBcu5Dp0ffIem06cwWu7/4TWYBRcJQAz+lyLoe1aeK5hXkKxvzk7d+6Mzp07AwAKCwuxZ88epS5N5Dx9rbZ5+1hCpAHKLa7GL6cKkVtcbd8JAdAVBA4FoLZxrAvlFxQAAGJjYjyyF/SIoUMBALt/+83oeX1Zg0uXL0OrNR931kJANYJRgTDUIhCAgMhI3TlKBany8nIAQEiI9f+fQ0PDAABlZWWKvC+51+XySrPwBgBaEXht92H2xEHhQYMpU6ZI91988UUlL01E5JAv9uWiz+LfMGHFH+iz+Dd8sc+BAKGGVwQ5V6qsrMTyN9/EgKFD0TglBYGxsdLODal9+gAAci5cMDonrX9/BAUF6ea1DR2KTz7/HDm5ubLBTW/IEN0Q8NSpE/HCC7Owd+9vLDPVAOmHQu0NXudLys3Cm55WFJFTUqFg63yTogFu2rRp6NOnD0RRxJYtW/CUzARYIiJXyy2uxux1J6RfAFoReG7dCft74vQ8FOTiGjUCABQWFblkFWXuhQu4/qab8K/Zs/Fzejou5+UhODgYCfHxSGzcGPFX5pbpe7v02l5zDd5ZvhyhoaHY9csvuG/yZDRt1w6tu3TB9JmPIyPjkNl7LViwFDfccBNKS0uxfPkSpKXdiOTkKAwfPggffPAOKisd60kJDw8HAFRVWT+vslL3Cz7CR0qr+LNNJ87gvjXb8MymPbhvzTZsOnHG5jlNo8KhstD5rBIEJEeFKdxK36NogFOr1Vi/fj369u0LURSxfPly9OvXDzt27FDybYjkOTJcqmTNONaf8zpZeRVmf71rRCA7z8mvj5uDXMf27QEA1dXVOH7ihOLXn/nsszhx8iRap6Rg7SefoODMGZRduIBLWVm4cOoUftu2zeK5kyZOxKnDh7FsyasYPvwONGoUh9Ons7Fy5bu4+ebuWLp0odHxcXFx2LIlHd99twWPPPI4unZNRU1NDXbu3I4nnpiGG27ogvPnz9nd9iZNdHPfcnNzLB5TWVmJoqKiK8dzgZ0nmQ6F2jsEmhAeihl9roXKZAqBShAwo08XJIRzSoyiG4/Onz8fANC/f3/89ddfuHjxInbv3o20tDQkJiaiR48eSElJQVRUFAIDAx269gsvvKBkU4nIj6XEh0ElwCjEqQWgVXw9f+jrg5x+iy4XLXbo37cvBEGAKIr4buNGdLgS6JRQU1ODb7//HgDw6QcfoHevXmbHXLx0SfZc/eKEyMYpmDrtX5g67V8QRREHD+7Hq68uwvr1X2PBgucxdOjt6NLlOuk8QRAwcOBgDBw4GIBunvTXX3+JefNmIyvrb8ya9QQ+/vhLu9qvX2F68eIF5Ofny65ENVx5yhIiniU3FKofApULYZfLK3G+pBxNo8IxtF0L9GiagJySCgQHqFBdp0VyVBjD2xWKBrh58+YZTbjV/wACgAsXLuD7Kz80nMEAR4ox3B+V/FJSdDAWjWmH59adgEbUhbeFY9ohKVqhPS5dHOSaNW2KYUOG4Psff8Qb772Hhx980Oa+iICuCoCtRQ95+fmortYNJad27Sp7zE8moyZaqK7sVRoAmOyaIAgCunfviY8//hKdO7fC+fPn8Ouv6UYBzlRsbCwmTZoCQMSMGQ8jPd1y4WBTN97YF4GBgaitrcWOHT/hzjvHmR2zdetmALqVqu3bd7T72qQ8/VCo8UpS+SFQw1WnhqtNGdjkubzykSAI0s0ZrKJNRM4Y1zMJ6bN647PJXZE+qzfG9XTBUJoLh1YXvPACgoODce78eUyYNAlVVVVWj1+zbh3+/cYbNq8bGREh/Tz+MzPT7PXcCxfwxrvvSo+rEIwKhKIWgaipsbz4QK1WSyMr+oCo1WpRV1dn8Rz9StKaGvvnJkZHR0sLI958899mq2HLy8vx4Ye69t9113iPrOKlq0yHQi0NgTo71NqQKR7g9NtpKXUjInJWUnQwbmwTo1zPmyWGQU6hcY3rr7sOb736KgRBwPc//ojUPn3wyeefo+BKiREAKC4uxrpvv8XAYcMw7v77UWpHyYzIyEj0vlLbbdK0aTj0xx8AdGFr644d6H/bbTD80VtnsKp03rzncO+9d2H9+m+M2nHp0kU8/fTjyM7OgiAIGDRItxNDSUkJuna9BkuXvozMzD+h0Wik99qxYyvmz58DAEhLu9Whf5s5c15CYGAg9u/fi4cf/qe0FdfZs2dwzz1jcPbsGcTExOCJJ5516LrkGkPbtcDHYwdi6dDe+HjsQNkabtaGWo9dLsRXh0/h2OVCAI6vaPVXig6hbt++XcnLEXkXw6HX53ayrhyZU1+5aaArCGy588kuD95/P+IaNcLUGTNw7MQJ3Dd5MgDdykpBEKTtqQCgZYsWGNTPvqkByxcvxsDhw/FnZiZS+/RBeHg4tFotKisr0Si2Ed56eyXGjx9tdp5GU4dvv12Lb79dC0BXF04URaN2PP/8AnTq1EV6fObMacyfPxfz589FYGAgIiIiUVJSLIW5lJTWWLTo3w79u1x7bVe88cYKPProQ/jss4/x+eefICoqCsXFxQB0K1U/+WSttMk9eV5CeKjVoVBLQ63fHc3Gruyr5Ww6NY7BsctFZsOsDZGiAa5///5KXo7I/RjSSAkKBrlRI0bglkGD8N/Vq/H9Dz/gj8xM5OXnQxAEtGrZEj1SUzFm5EiMGTkSwcH29TTe0LMnft26FfMWLsTPu3ejvLwcTZokYfDg2/D003OkcGVq+vQnkJLSBjt2bMXx40dx8WIuqqur0axZc9xww02YPHk6+vS5WTo+KioKX365ATt2/IQ9e37B+fPnkJd3GeHh4Wjbtj2GDx+Fhx9+DJGRkQ7/u9xzz/3o2LEzXnttKXbv3onCwgI0a9YcAwfegiefnI02ba5x+JrkGfqFCw/26ICV+49DK4pQCQLGXdcan2WcMjr2yKUi6b5+mLVH04QGOU9OEDlO6XdKSkoQHR2N4uIDiIrysRpI7ghQposYDN/H2vtbes3a9Rqw6motzp6tQ/PmyQgODvJ0czxLoR45pWmgQi2CUKfs3/I+qaamGjk5ZxEQ0BwqlYuH3EliunBhUo8OaB8fg+SoMPyclYP39x6zeY2lQ3uja5L8vri+pqysBN27R6O4uNjmwiUv2r6ZCMZ11OypqVbfGmxKhK2gUN11lGoT+R81gBAoOkeuPjRQoQohqEQYwxt5jNzChQ/3H0dwgEoqJWJLQy7qywDnJS5cuIAZM2agTZs2CAkJQWJiIkaMGIGtW7d6umlEpBQPBzkGN1JSfRcTWFq4MGP9L3hm0x68tPUAOjWOsXi+bg7c1RWtDW1xA/8P9gJ//PEHBg0ahPz8fAC6eSN5eXnYsGEDvv/+eyxcuBCzZs3ycCt9wMJ+lnvUTIc/5+1zb9uIDCm82MEWDpWS0izVbHNESIAaAgDTeVz6x1oROHa5GP9MbYdVv5vvSDK7fyr6t05WrD2+hj1wHlZZWYmRI0ciPz8fqampOHz4MIqLi1FYWIgnn3wSoijiueeew+bNmz3dVM/gcCT5M32PXBhc8ue0BmpUsseNFKZEzbZNJ85g5oZfjMKbXMU+rSiiaYz5vqgqQUCnxFjF2uOLFP0/etKkSUpeTiIIAlauXOmSa3vae++9h9OnTyMiIgLr169H06ZNAeh64ZYtW4ZTp07hm2++wezZszFkyBAPt9aPyO3GYDiPjcidVNAFOS10PXKW6+XaRQM1ahAEjTs2biW/Z7i9VUJ4qMPbY8ldzzBwAbrwNm9wd7y09YBZKZFOjWMxo8+1eG33YWmFquHQaX3b46sUDXCrVq1SvOq1fmsYfw1wn376KQBgwoQJUngz9PTTT+Obb77BwYMHcfz4cbRXcE9En2UYvp760f5j6yso1Hjo1ZF2ENlDBSAYQCCcCnIMbqQ0uaHJHk0TzGq2AcCJvCIkR4UZhT09wxAoF7hEAGGBgUhr0xRbTp6Xnk9rk4yE8FBpX9QjlwohiiI6JzaSjnFkuy5/4lV96qYVTfx9C5TS0lIcOHAAAHDrrfKVyHv37n2lJEgxtm7dygDnaqYhTQ73UiVXczDIMbiRK1gamvx47EBM6tEBH+wzLvHxwb5j+GDfMYgwnodmGgIf7NFBNnAFB6iw9dR5o2tuPZWDf3Zvj4TwUOw/f9niXqnWeuj8leIBrr5l5fShrSFspXX06FHpM3bu3Fn2GJVKhfbt22Pv3r04cuSIO5vnG5bZ2ILHXfPmDIMf5+qRUmwEOQY3ciVrQ5Pt4qPNjheNjtOFvZTYSPwn/U+jhQkr9x/HuOva4POMU1fCni5wVdVpLL4fANkwqS/iq++hyympQHJUmN+HN0DhAJeVleXwORUVFbh8+TL27duHL774Avv374cgCLjmmmuwcuVKtGjhv6tIcnNzpfvJyckWj9O/Zni8oerqamnzaEBXyNdnGa4gtbc+21M/2g5y7mRPLx6RI0yCnKaWwY1cz9bQpNwwqiGtKOLTQ3+ZrTLViqK0w4IA4MEe7TG0XQtcLq+0+H7WwiQAaXjWXwr62kPRANeyZUunzuvYsSP69euHJ598EuvWrcPkyZNx6tQpjB8/Hj/99BM6dOigZDO9Rnl5uXQ/NNRyWAkL0/3PUmZho+pFixbhpZdeUrZxROR9rgS5ak0wtFoWESD7mC5CsJetoUnD1/QTnkzD2p6zl62+hwhdj9yA1sk2308u3J3IK8KzP/zWoMqH6HnVHDgAGDNmDJo3b44BAwYgJycHw4YNw6FDh2xuKdGQzZ49G//617+kxyUlJWjevLkHW+QB9vR4PfWjrneM89eIqIGob300a0OTPZomYFb/6yEA6JQYi+1/55jNi7OH4YpRS+8nF+4m9WiPlfuPWRxW9XdeF+AAoGfPnnjqqafwf//3fzh9+jRefPFFLF++3NPNUlx4+NVtQiorKy1u6FxRoesijoiQ39c0ODjY7k2sfY69w5H27KHqymFWV+/fSkTkIEuLEBwNOAnhoWbHywVDuXlx9goOUEltNtxG61BuntRzaBruLA2r7szKRb+UJL8PcV4Z4ADg4Ycfxv/93/9BFEWsWLECCxcutDrM6IsM573l5ORYXGGak5MDAEhKSnJLu3xOTZVzoUkftvThz9pODkREPsZV9dEsBcP/3H6j7M4K9pi54RektWmKrafOQyvCaEhWAPBgzw4Ye20bszApNw/vvb1HsWLfUb8fTvXaSRRJSUlISUkBoOud2rnT/4qsdujQQVp1m5mZKXuMVqvF8ePHAQCdOnVyW9u8WlAo8Pi3ll9f2E+3c0NZgevD2HM7WQCYiLySfhGCISXqo1kKhtV1WjzUU37Ouq2iYFoR2HLyvHRdEVeDoAhdiZIv/zxldI5+WFUlU3KsIezG4LUBDgASEhKk+8eOOT6u7u0iIyPRo0cPAMCWLVtkj9mzZw+Ki4sBAGlpaW5rW4NiWPbD9L7cNl76Yd15+9hbR0ReyzTgKFUfzVowtHTtR3t3thnibPlg3zGzQDa0XQt8PHYgpvbqaHa84SpVf+TVAc5w1aV+Hpi/mTBhAgDdjgxyZUKWLVsGAOjevXvDKOJrTziqqQRev8PgnBD54/Rz3ubtYy8ZETVI+oCzdGhvfDx2oCJDipaC4f7zl7Fox+9mxwsARMG5oVVDIiAbyBLCQ9EvJcklvY3ezGsDXFFREU6cOCENMcbExHi2QS4ydepUtGzZEqWlpbj99tulYr2lpaV45plnsG7dOgDAwoULPdlMz7O2qX1NFVeWEsmIjBQQGSng9OlsTzeFPCghPBRdk+IUndRvGgx7NE3Aa7v/lA1pIoA3f820qwfO2jGmgexyeSUO5ebhcnmly3obvZnXLmJ45ZVXUFdXB0C3O4N+Ppy/CQ0Nxbfffou0tDQcPHgQnTt3RlRUFMrKyqDVaiEIAhYuXMiN7K2prXLuvJpK54ZAywqu9u7pS5MQuVBFRQX++9/V2LjxR2RkHEZeXj4EQUBCQmNcf3133H77KNxxx51+t9DLkvPnzyE9/WccPLgPBw7sw59/HkJFRQUaN07EqVMXPN08vyRXS85wQcGh3DyrRX2BKwsSBMDaJksigEFtkvFgjw54d88R7Mq++vXU74sKWC6P0pB2Y/C6AKfVavHKK69gyZIlEAQBoigiODgY/fv393TTXKZr1644fPgwFi1ahA0bNuD8+fOIi4tDr1698MQTT3Dumy3vjHPuPFcFL3tKmhDZaf36jZgy5XFcuHBRei48PBwqlQqnT2fj9OlsfPvtWrzwwrNYseJj9O8/yIOtdY/XX1+Gt99+zdPNaDAshSXDUCe3a4OcR3t3Rm5pBb46bHnnpm2ncpAYEYrdp43DuH5fVMD6tlr+Htz0FA1wzq4UraysxMWLF/H777/j66+/xtmzZ6U9QgVBwIMPPuj3f1k2adIEr732Gl57rQH8UPJEwAkK1b2X6VBrTaVxfbgaB3vzaqqunm9YloRIAatWfYIHH5wOrVaL9u3bYu7cZzB06C0IDW0OrVaF4uJi7NjxE957703s2rUDu3fvbBABThAEtG7dBqmpPdCtW0/k5ubgzTf/7elmeR1nd2AwvYZcWCqrrpWK6OpDndwG96YKKqpxbZNGVgMcAGmfVEP6RQkiRJeUR/E1iga4AQMGSHPWnGUY3ERRRJs2bTB//nwlmkcNmWFo1JObN2dpQYRS7y0XWNljRzIyMv7Eww/PhFarxbBhQ/DVV59If8jq13RFR0fjjjvuxB133Im1a7/A+fPnPNhi93n55WVYvPhqcfdPPlnlucZ4qfruwKBnqWTIB/uOGW1Q/5/0P+263qcZJ+06Tl//zfCtre3D6u8LFuS4ZBGDKIpO3QBIAVAURaSmpmLLli2IjY11RTOJzC271bEeNMPVsPr6c+yBIwXMnTsf1dXVaNo0GatXf2hzFOLOO8fhscf+ZfUYPY1Gg82bN+Hxx6fi5pu7o3XrRDRqFIS2bZMxfvxo/PzzNovnarVafPLJKgwbNhAtWsQhNjYQrVoloGfPznjkkUnYsuUHs3Oys7Mwc+YjuP76dkhICEXjxmHo1Kklhg4dgGXLFiEvL8+uduup1WqHjm9oLPWaWauJZrggwNBfecWyx5v2jokyz9WHStAV75VblGC6YEEAMKlH+wbV+wa4YA6caG12op3npqamYvLkyZg8eTL/RyXPsXcbLyKFnT+fg++//xEA8PjjDyM62r4tiuwdATl+/CjuvHOY9DgqKgpBQUG4cCEXGzZ8gw0bvsGLLy7EU0/NNjt38uT7sGbNaulxdHQ0SktLkJ+fh2PHjuDYsSO45ZbbpNcPHTqIYcMGoLS0FAAQGBiI8PBwnD17BmfPnkF6+s/o2jXV6ByqH0d3YLA2x23lfs/UYL25VRIGtk7GwNbJsosShrZrgbLqWqkn8MP9xxAZHOjXOy+YUjTAvfjiiw6fIwgCQkJCEBUVhZYtW6Jbt25ITExUslnkSc4MD9o6x9J8NlPODke6YzjT8DM+9aNr3oN81o4du6Q/aEeOHGbjaMcFBgbhvvsm4c47x6Fnz96IiooCAFy+fAkfffQ+Fi6ch/nz56B//0Ho2fMG6bz09J1Ys2Y11Go1Xn55GSZOfBCRkZEQRREXL17A1q2bkZlpPJQ2Z85TKC0tRY8eN+A//3kHXbumAtCtrD127AjWrPkUUVHO76FJ5uQWFFgaYrS2X6pcEJRjuO2VUn7OysXOrFzc2SUF/VKScL6kHACkEKcPl4bDuA1pI3vACwIcNSD1CSymvWHuGKY0LTMiN4+OvFdNBbCwre7+c38BQb4zP+boUd32ecHBwWjfvp3i12/bth3efnul2fMJCY3xzDNzIYoiFix4AStXvmsU4Pbt+w0AMGjQLZg+fab0vCAIaNIkCffcc7/ZNfXnvPLKa1J4A4CwsDB069YD3br1UOpj0RX6IcbXdh+GVhSt1kSz1ltnz8rSER1a4Ja2zZBVWGrwfroeso3Hz9Qr1IkAvjqcJS14MOwddNU+r77Eawv5ElmlD3Tu7L0yDI3W9mIlqqf8/AIAQGxsTL0Xhjlj6NARAIDffttt9LxhT51Wq7XrWpGRunMuXDDfaYZcx94dGGxti2Vpr1G99cfOYOaGXwDA4P0GoX/rJIfCmwDgnuuvsXqM4Vy+kAD56VXBAQ0n1jScT0q+w9LepHIMe8jkNpbX7+Dgzp4z7pVKPqCyshJvvrkcQ4cOQEpKY8TGBko7N/Tpo+spu3Ahx+ic/v3TEBQUhEOHDmLo0AH4/PNPkJubI3d5yZAhuiHgqVMn4oUXZmHv3t9QW1vrmg9FRuzZgUFuQcCDBgsCDIPgQwaLCgzpgxUA6f3kgqE1fVs1QcuYCDs2vdf1slXVaWRfr66z7w8Lf6DoEOr//vc/6f6tt95ar7lsFy5cwObNm6XHEydOrFfbyIt42+KAR76QLwZcU6ULf4B5MDTd/eHxb6+uSHV2hweiK+LiGgEACguLIIqi4r1wFy7kYujQATh58oT0XHh4OGJiYqFSqaDRaJCfn4fy8nKj8665pi2WL38HTz31KH75ZRd++WUXAKBly1YYPPg2PPDAFKNhUgBYsGAp/vrrOPbs+QXLly/B8uVLEBISgl69bsTo0f/APff80+/rfHq7oe1aoLS6FiuvLAhYuf8YIgwWBOhXfnZNisPA1snYmZWL9/YeNbqG6fCl6TCuaUkQU7uyL2BX9gWbAY6lRK5StAfun//8Jx544AE88MADyMzMrNe1MjMzja5HpAi5IddAC7XfDEuE1IetHjn22JGJjh111earq6tx/PgJG0c77tlnZ+LkyRNISWmNTz5ZizNnCnDhQhmysi7h1KkL2LbtN4vnTpw4CYcPZ2HJkv9g+PA70KhRHE6fzsbKle/i5pu7Y+lS432b4+LisGVLOr77bgseeeRxdO2aipqaGuzcuR1PPDENN9zQpcHUr/NWl8sr8aHMggC5siOWNo4XYD58adh799qIm+zqkbMW8kzn8o3pnCIFvoaw96kpxYdQ61NGxB3XowbOcNcFR5ju2GAa+gwLANu70lbuPhGA/v37Sr1u3323UdFr19TU4PvvdXM4P/jgU9xxxxizWpuXLl2UO1XSuHEipk2bgc8//wbZ2ZexY8dejBgx+srih+dx+PAfRscLgoCBAwfjlVdeQ3r6QWRn5+G1195DbGwjZGX9jVmznlD0M5JjrC0IkCM3N04EMGP9L9h04ozZsV2T4tAhIdbmfDprHu7VUZrLt+nEGdy3Zpu0uOEfXVpbnefnrxQPcJ6YcEteRD/nzBUFbe25tiO9Wc/tvHKcHbsvOBv8iJzQrFlTDBs2BADwxhvvoaSkxK7z7PmDNz8/D9XV1QBgNtypt2PHT3a2VPczv3v3nvj44y/RtGkzaLVa/PprutVzYmNjMWnSFMybp+utS0//2e73I+VZW8hgydB2LfCf2280ek6EbkcGSwWD9edM7dUR47u2sTvMqQQBN6ckISE81KzsiQhgbab1bbn8ldcuYjD8QcRQ6MP0gcp0Dpmtc+TuW7u+rw0/OvIZqUFasOAFBAcH49y585gwYRKqqqzv07tu3Rq88Ybt/UAjIiKln6mmNdsA3fy4d999Q/bcmpoai9dVq9UIDAwEACkgarVa1NXVWTwnJCT0ynWrbbabXMe0R83e4cgLpeY9dCKAIxcLZY/fdEK3YvW9vUfxxR+n8GCP9pgzIBUDWycbDYXeck1Ti21xtLfQnym+E4NSysrKpPvh4eEebAkpwpsWLjz1o65HbWE/+WCpf87aylVX7JlKygoKA+ad93QrnHb99dfhrbdexeTJj+H7739EamofzJnzNIYNG4KQEF3PiG4z+6147703sGvXDsyebbsWZ2RkJHr27I29e3/FtGmT8P77/8N1110PrVaLnTu3Y+bMRyz25M2b9xzOnMnGuHH3ok+ffmjUSLfY4tKli1i69GVkZ2dBEAQMGnQLAKCkpAR9+lyPf/5zMoYNG4kOHTpBrVZL7zV//hwAQFqaYz3ctbW1KC6+usVTebnu94UoikbbcqnVam7FaKeh7VqgR9ME5JRUIDhAhao6DS6XV9oIcRY6V2SelisYbLifqt6DPdrjH9e2wT+7t5fdgcGRIsX+zmsD3B9/XJ1Dwf8Bya1M57uZMg19jvQuEjngwQfvR1xcI0ydOgPHjp3AffdNBgBERERAEARpeyoAaNGiJfr1G2TXdRcvXo7hwwciM/NP9OmTivDwcGi1WlRWViI2thHefvtDjB8/yuw8jaYO3367Ft9+uxaAri6cKIpG7Xj++QXo1KmL9PjMmdOYP38u5s+fi8DAQERERKKkpBgaja4MREpKayxaZLvn0NBvv+3GsGEDzZ6/fPkSUlISpMctWrREZma2Q9duyBLCQ7H//GXZbbXkdE6U/93cqbH583I9Z3J/Jnyw7xiubdIIHRJiZcOjtSLFl8srcb6kHE2jwhvEYgavDHBZWVl4//33pW7+Tp06ebhF5FZK9NaZbscFWO5R4xAmebFRo0bgllsG4b//XY3vv/8Bf/yRiby8fAiCgJYtWyE1tQdGjhyDkSPHIDg42K5r9ux5A7Zu/RULF87D7t0/o7y8HE2aJGHw4Nvw9NNzpHBlavr0J5CS0gY7dmzF8eNHcfFiLqqrq9GsWXPccMNNmDx5Ovr0uVk6PioqCl9+uQE7dvyEPXt+wfnz55CXdxnh4eFo27Y9hg8fhYcffgyRkZGK/FtR/VjbVstSQDItD2JpwlNIgNpmKRHg6mKImX2Ng6Phexv2Fup76Czt5+rPHA5wkyZNsuu4pUuX4pNPPrH7uqIooqKiAllZWTh06BA0Go1U/2jgQPO/tIic2mdVjr17q5qeYxoyvWWImPxOeHg4pk2bjGnTdD1wFRVh0GptT2EuLbX86/Laa7vis8++dujcFi1a4uGHH8PDDz9mR6sBlUqF224bjttuG27X8fa6+eYBVj8bOcfa/DLDnjkBwJ1dUtAuPsYskImA2XZW+nBlGvQsfQVFGAdHS+HMcF9Ua8HTXzkc4FatWmV1UYF+7oRhEV5H6M/Xv0dERASL+FL92BoSBYwDmeEKV/18OSIiP3cir9jsOZUgIDhAZbbyU1/CwzSImc5HMw1XeqLMuYYMFybYCmcNdV9UrxtC1Qc3URQREhKCjz76qF47OhAZqc98tfr08pnypkUdRNTg6Yv5mnqwR3tU1WmsbmivX1Qgt3pVLlzpWQtx+iCYebHAZjhrqAsbnApw9tQacrYAr1qtRrt27TBkyBBMmzYNbdu2deo65CGuDCam13ZHAVwGLSJqACwFrXbxMUiOCjMLSHoigOf6pyImNNhsxSggH65MzzelGybtgv3nL+M/6ealbkzDWUJ4KCb16CBtBdZQdmVwOMBlZckXzBNFEa1bt5Z60D755BPcdNNNdl9XpVIhPDwcUVFRCAjwuo5B8mU1BvWzuE8pEZGRy+WVKKqssTgcenXlp/lQqEoQ0ClRfsWo3pjOKViXmWW1F8/Q7P6p6JQYi/vWbDMLeAKAST3a43xJOfIrqlBVp8FfecXSVmACdL2G/r6AAXAiwLVs2dKu4xITE+0+loiIiNzPcIGAgKtDmqa9WPqVn19nZmHt4Sy7erpMr31XlxTEhgZj5f7jV0qAAKJoHho7JcbKDp0CwLD2zfHh/mNWe/RW7j+OAa2T2QPniBYtWkg9cKGh/v0PR36Mw6ZE1ADIbUulEnRDonK9agnhoZjSqxNGd06RLbJr6NjlQvwn/erKUxHAusxsfDx2IAa0TpbO161uNa7pZnnoFNh4/KzNUiQNYQEDoHCAy87OVvJyRM4zDGFlBZ5tCxGRF5JfvQnEhAZbDT8J4aFWX9904oxReLt6bV2w6poUZ9azpw90ACwOnY7pnCKtfrVGABAc4LU7hSrG/z8h+S9f3QeViMgLOLOJvS36Xj1rK0tNJYSHSqHO0mKK5wamYnTnFIuFgg2JAGZu+AWbTpxxtPk+hQGO/B83jvcoJxekE7lZw/tGdXYTe2ssBTABsOvalkJlp8ax2H/+suw5KkHA+K5tjMKdvl7c5XI3VCvwEC73JCKXUF3589DStkxE3kSr1V6517D6NeS2paoPubIhAoDXRtyEDgm29zW3tNcpAPPdHAzm650vKcdnGaeMruXvc+EY4IjIJQICBAQEiKioqEK4n/4AJf9RU1MJUVRBEPzz16K1jd5tzWlzhKUAZk9405MLlYdy88x3czCZr9fQivm6/Dv12LFj+OWXX/D7778jLy8PRUVFqK6udugagiBg69atLmoh+T1PFAAmCIKAiAgVSkrKEBkZjpCQIE83iUiWVqtBeXkpgDCrW0X6Kndv9K5Er55pqLS124Kl4OivvW+ACwPct99+i8WLF2Pv3r31uo5+Q3sixbBMiNs0ahSAqqoa5ORcREREBMLDQ6BWq8H/peunpkZt12b2ZIuI2toalJYWoapKi8DAOE83SHGe2uhdyV49/fXS2jTFlpPnpefS2hjXelN6ONjbKR7gNBoNpk6dio8++giAcQAz3F5LLpTZep2IfItKJSA5OQgFBXUoKytCSQn/v1ZCdXUwRJH/lkrQ/doJRUBAY6hUgZ5ujuL8ZaP3y+WV2HrqvNFzW0/l4J/d2xt9DqWDozdTPMDNnDkTH374IQCYBTfDUCa3V6qt14nI96hUAuLjAxEXJ6KuToQ0V5ycdu5cE9TWckhaCYKg9tt5b4D/bPTuL0FUSYp+1/7888946623pCAWFBSEp59+Gvfeey9atWqFkJAQ6bWffvoJffv2RUFBATIzM7Ft2zZ8+OGHuHjxIgRBQKdOnfDpp5+ia9euSjaRiDxEEAQEBrLXSAlqdTA0GgY4ss1f5ob5SxBVkiAq2NV12223YfPmzQCAgIAAbNy4EYMHD5ZeV6lUUoDbsmULBg0aZHR+TU0N5s6di1dffRUAEBERgQ0bNuDmm29WqokNQklJCaKjo1FcfABRURGebg4RKSw7uxVqahjgyH6Xyyt9fm6YbjGGcRD1t03ry8pK0L17NIqLixEVFWX1WMV64MrLy7F161YpoE2ZMsUovNkjKCgIr7zyCtq0aYNHHnkEpaWlGD16NDIzM5GYmKhUU4mIiBoUf5gb1tAWKdii2DKm3377DRqNRpq79vDDDzt9ralTp+If//gHAKCwsBDPP/+8Im0kIiIi32W47VZDp1iAO336tHQ/OjoaXbp0sXq8rVpwc+bMAaBbzPDpp5+iqqqq/o0kIiIi8gOKBbiCggIAuonKLVrIj0kHBFwdsbUVyK677jpp2LSqqgq//PKLQi0lIiIi8m2KBbi6ujrpfnh4uOwxkZGR0hDrpUuXbF6zWbNm0v3jx4/Xs4VERERE/kGxABcdHS3dLysrkz0mJiZGum845GqJ1qBgVFFRkdNtIyIiIvInigU4/bCpKIrScKqpDh06SPf37Nlj9XoajQZ//fWXtKo1ODhYoZYSERER+TbFAlznzp2l+zk5ObK9cNdffz0AXchLT09HTk6Oxet9/fXXKCsrk4Zck5KSlGoqERERkU9TLMC1atUKTZo0kR7v37/f7JhRo0YB0C10qKurwyOPPGI0d07v77//xowZM4y21urTp49STSUiIiLyaYoFOABGOyts3LjR7PWePXvi2muvlR5v2LAB3bt3xxtvvIHNmzdjw4YNmDVrFrp164YLFy5AFEUIgoB+/fpZXNlKRERE1NAoupXWunXrcNddd0mlRP7++2+jXjQA2LVrFwYMGABAfpN7/fOCIEAURQQFBWHnzp3o1auXUs30e9xKi8i/cSstIv/kyFZaivbADR8+HN26dUOnTp0QEREhW7vt5ptvxttvvw1AF9z0QU1/0z8viiICAwPx/vvvM7wRERERGVBsL1RAt1JUbu6bqalTp6Jdu3Z48skncejQIaPX9CHuxhtvxLJly3DjjTcq2UQiIiIin6dogHPEwIEDcfDgQfz111/47bffcPHiRYiiiCZNmuCmm25CmzZtPNU0IiIiIq/msQCn17ZtW7Rt29bTzXC7HTt2YODAgTaPu3z5MuLj493QIiIiIvIVHg9wDZ1KpUJCQoLV14mIiIgMMcB5WPPmzZGdne3pZhAREZEPYfcOERERkY9xWw9cQUEBjh49ioKCAhQXF0Or1eLWW29FYmKiu5pARERE5BdcGuAuXbqEN998E2vXrsWxY8fMXt+yZYtsgPvoo49w9uxZAEBycjIeeughVzaTiIiIyKe4LMAtXboUL7zwAmpqaiC32YPp7guGysrKMG/ePAiCALVajREjRvhtT93ly5fRrVs3HD9+HADQtGlTDBgwAI899pjRtmNEREREeorPgdNoNBgzZgxmzZqF6upqs9etBTe9Bx98EFFRURBFERqNBqtXr1a6mV6joqICv//+O4KDg1FXV4e//voLK1asQGpqKpYtW2bXNaqrq1FSUmJ0IyIiIv+leICbPn06vvnmG6P9TFNTU/Hss8/irbfeku2NMxUWFoYRI0ZIjzdu3Kh0Mz0uJiYGTz/9NPbv34/KykoUFBSgoqICP//8M2666SZoNBo8/fTTdoXXRYsWITo6Wro1b97cDZ+AiIiIPEXRzezT09PRr18/qZctPj4eq1atwtChQ6VjVCqV9PqWLVswaNAg2WutXbsW//jHPwAAISEhKCoqQlCQZzdvnj9/PubPn+/Uuc8++yxefvllu46tqanBoEGDsHv3bjRr1gynT5+2Wg+uurraqLezpKQEzZs352b2RH6Km9kT+SePbWb/wgsvANDtZxoZGYmff/7ZKLw54oYbbpDuV1dXS3PEPEmr1UKj0Th9s1dQUBD+7//+DwBw7tw5/P7771aPDw4ORlRUlNGNiIiI/JdiAa6wsBC7du2CIAgQBAFz585Fhw4dnL5es2bNEBsbKz2WW8XqbvPmzYMoik7dFi9e7NB7GQbYv//+W+mPQkRERD5MsQCXnp4OjUYDURShUqkUKf3RuHFj6f6lS5fqfT0iIiIif6BYgMvJyQGgW2XaunVrxMTE1Pua0dHR0v3S0tJ6X8+X7NmzR7qfkpLiwZYQERGRt1EswBUUFEj3GzVqpMg1DSfmBwYGKnJNb2Ft7Uhtba00nzApKQndunVzV7OIiIjIBygW4FzRW2Y4bBofH6/INb1Fly5d8MYbb+Cvv/6SwpxGo0F6ejrS0tKQnp4OQFcixNoKVCIiImp4FNuJISEhAYCuZ+n06dPQarX1Ch5nz55Fbm6u9Dg5ObnebfQmR44cweOPPw5At4o0MjISJSUlqKmpAQAEBARgwYIFuP/++z3ZTCIiIvJCigW4rl27SvcrKiqwe/du3HzzzU5f78svv5Tuq9Vq9O7du17t8zbvvfcedu/ejQMHDuDSpUsoLCxEaGgo2rdvj/79++ORRx5Bp06dPN1MIiIi8kKKBbh27dohJSUF2dnZAIB///vfTge4kpISLF++XCr427NnT0RGRirVVK8wZcoUTJkyxdPNICIiIh+k6OSqiRMnSnXPvvvuO/z3v/91+BoajQYTJ07E+fPnpblh06ZNU7KZRERERD5N0QD31FNPoXHjxtIeqA899BCWLl1q9y4Ex44dw6BBg7B+/XqpIHC7du0wYcIEJZtJRERE5NMUG0IFgPDwcHzwwQcYPXq0tO3UrFmz8Pbbb2P8+PHo3r07AEgb3R84cAAFBQU4efIktm3bhm3btkk9eAAQGhqK1atXS0OpRERERKTwZvZ677//PqZNm2YUxvQhzPDtTIOZPtiJoojAwEB8/PHHGDt2rNLN83slJSWIjo7mZvZEfoqb2RP5J49tZq83ZcoU/Pjjj0hMTARgHN70Q6P6oGYa8kRRRGJiIrZu3crwRkRERCTDZRVi09LScPToUSxcuBBJSUlSSDMNbXqiKCImJgYvvfQSjh8/jr59+7qqaUREREQ+zSVDqKa0Wi0yMjKwa9cuHD16FPn5+SgqKkJYWBji4+ORkpKCgQMHolevXggIUHRaXoPEIVQi/8YhVCL/5MgQqlvSkkqlQmpqKlJTU93xdkRERER+jZtsEhEREfkYBjgiIiIiH+PQEOq//vUv6f60adNwzTXXKN4gIvI/ucW1yMqrRUp8IJKiAz3dHPJjQl052q5JBgD8NTYHYkC4W88ncheHAtx//vMfqSTI7bffbjPAFRcXIyMjQ3rcr18/J5pIRN7GkUD2xb5izF53CVoRUAnAojGNMa5ntJtaSkTknxxexKCv5WaP/fv3Y8iQIQB0Nd7q6uocfTsi8jKOBLLc4lrpWADQisBz6y6hX7sw9sQREdWDw3PgHN3WylLdNyLyPZYCWW5xrezxWXm10rF6GhHIzpM/nsgbCXXlaLc6Gu1WR0OoK/eaa1HDxkUMRGQ3RwNZSnwgVCZ/86kFoFU8e9/IN7Vdk8zwRV6BAY6IAOh61345VWGxNw1wPJAlRQdi0ZjGUAtXj104pjGHT8lp7MEi0uG2B0Rk97w2fSB7bt0laET7Atm4ntHo1y4M2Xm1aMVVqEREimCAI2rgHF1o4EwgS4pmcCP/Zq38iOFrJ8ec9Ej7yP8wwBE1cNbmtelDl2nZEAYy8lZiQDhOTCj22PlE7sIAR9RA6UNZeJAAlQCjEGc4r83S8CqL8xIReQ4DHFEDZBrKRqdG4pvfS83mtckNr85edwmHzlbhi30lLM5LXoW7KFBDwgBH1MDIhbJvfi/FumnNUFEjGs1rkxte1YrAZ3tLjB6zOC95u/qEO/2wquE1TK9p79w2MSCMQ7SkCAY4ogbG0py3ihoRN7YJM3peXzbE9HhTpnPmiLyNUFdhdN+Z3jnT+XHWyphw4QK5mtMBLiMjAwEB1k833AcVAHbt2uX0jgzcR5VIGXKhzFItN9OyIZa4ozgv59wR4LlFBt4wPOsNbSDv4VSAE0URTz31lMPnDBgwwJm34z6qRApytJabvmzIwdOVeHT1RZjmOAHAg31jXNpmR/ZfJfJVDGjkCKcCnCAIdvekGe6dyv1QibyDrVpucmVDhl8XiLJqUQp+KgB924Yi/WQl3t9VhA/Si1wSrBytU0fkCaZz2wyHVznvjVzB6SFURze1d/Ychj4i51kbdrRUy81ab5dh8AsLEjD67XNmK1SVDlb21KkjcpTpggSgfr1eQl2FUe8Zkas5FOBatGjhVAgjIvdzZtjRnt4uffD75VSF7ArVj3YX4blhCTbbZ1iHrrxGtDi3zZE5e0REDYVDAS47O9tFzSAiJTk77OhIb5elFaof7CzCA31irL6PYbjUsxQyndl/lRomuVWi+l6xUyP/8FSziFyCZUSIfIw9qzEtBbED2VVoFHH1XNNrObpC9cG+MVixq8joeS2sD2+ahkvpPJOQadg2Z/ZfJTLU5rvrpPtiQJiVI+1nGBgN57y1XZNsFBidLVtCZA0DHJEPsXdYVC6ICQAe//yC0e4LX/9eanYtR3q7JvWNwQe7ioxWpqoA5JfXIbdYPsTJhUs9fW/fdxmlWLwpH6JJ2xjcqL7089ys1XCzxXS+m1w4MwyJSgVGIkMMcEQ+wpFhUdNhRxUAETA6d+3BUul4w2s50tuVFB2IxXdefR/hyvs8uvqixX1TrRUHVgtA+l/leGtHkWzbGODIUyztxmCJYeFge9kqNuypGnjknRjgiLyU6fCmo6sxDYNYfnkdHl190er7GV7L0gpVOfr3OZBdJfXwAVdWpa69hKJKDZZsyjfq6ZMrDqwWgGeGxmHxxnyrbbOGxX7J1SwFM1VVnsVz2q5JtmuFK3vtyBEMcEReSG6otF+7MIdXY+qDWG5xrc0tseqzsjMpOhCNImT2TQWwyCCQ6XvT0me1QvqsVlI5Ev0erFl5tWaFggHdv0GrePM5e4ZY7Ldhc6QIrr29aO7ibe0h36DydAOIyJiloVJAF0rUVyr5OLIaUz+kqrJQBUilwMrOlPhA2FNkyLA37cY2YejaPBQ3tgkzWkRh6tmhcdh5ogJ9Fmdjworz6LM4G1/suzqUZOnfLLe41unPQw3DX2NzcGJCMU5MKK7XQgP2mJG7McAReRlrQ6XjekYjfVYrfDa5KdJntXKoh2lcz2h8Pa2ZWchSAfh6WjOza+UW1+KXUxV2haCMs5XY8EcZujYLtnmstZ4+fdDUh1QVgNlD4zCya6TVgGbt34wanrZrkm1sNF8he98aoa4c7VZH45p115i9l6rqstnzhqteiVyBQ6hEXubPc1VmzxmGHkfmp5nq2jzUaNGBft5ZeY1otGrUkeHIJ9dcMFoQIUcF3XCqrV7D3OJaNG8UiHXTmknDqpaKBhv25LHYL8lxdOGBt+HeqGQNAxyRF8ktrsWSH8wn8T8zNE6xSfmGixv+OFdltsCgX7swu1e7ZpyttBneBADPDovDdU1DrK5qlQuNN7bRDUvZCmgs9ktyLAUga71uDE3kKxjgiLyIpRpp1zUNUfR99MHmng/OmwW118Yn2r3adW+2eW+hKRHAK5vykT6rld3FffVt6dAkSNpmy1ZAY7Ffqi9P9dQ5U3KEiAGOyIu4cyjQ0rwxiILNNuhXg8aE2rc3sqUAqL9OfplGti2j3j5nVMw3fVYrHDxdCa0ooEcr81Bbn+FlIlOGBXtPjjlp9ThDp0b+4fQcuJNjTkIbknDluvLz+EyDJnsKGyYGOCIvUt+hQEfqoOlXjRrmJkEAurcKkW0DAPxyqgJ/nqvS7ZLgwOdSyYRQ0yFT07YAgGjSI/fMbXFY8kM+S4U0MN44rHlyzEmzhQv65w1XpHpLe8n/MMAReRlnhwKVqIMmisCB05Xo1y5MqtPWKj5QKuFhrY6cNXf3jEJSdCAyzlZib3YVWscHmA2ZCgKgEnWLHeRoRBgFR+7QQIbEgHCjUKXbyeBqkDIOgPUvmCsX3pzFAr7kDAY4Ii/k6FCg3Byy2Wt1c8i6Ng+VPcdS0VzTbbAyzlZi1rpLUm+YMz7fV4I/z1fhz/M1Fo8RReCxtFg0jlRj7jfmVe3lChHbu0MD+QZv7GlzFcPPam14lsgSBjgiPyA3n00L3RyyxQ5seC+dKwKz113CobNV+HxviUPDpXK0IqyGN73XtxZaLAY8smsEvj1UZtQWlgrxXa4Ia/b2ZMntKWprAYNcj5u+3YZz1cSAMO5ZSm7BQr5EfsDSDgailR0JkqID8ezQOIu7M2hF4DMFwps1cm9t6f2+yzAObyoAz9ymXHkVIlNKrA7VFwButzraanFhOfogWN9dIsg/McAR+QH94ge5QKQRgYOnK812VfhiX7FUAw6QD1Ny7D3OHvaEQ+HKTa6HcckP+UZbahEZ0gegv8bmOHyu6Vw5a0x3djAObfIh0JndIIgMMcAR+RG5QCRAN6/NcA9R0zlzepZ64wz1bq1sTTpbHkuLtRj09EO9GWcr3dom8hxb22TZItRV2OwRc/f8OzEgjD1t5DAGuHqorq7Gjz/+iAULFuCOO+5AcnIyBEGAIAj44Ycf7L7Ol19+iUGDBiEuLg5hYWHo2LEj5s6di9JS6xXuifT0gUyOCJit3NyfXWUW3kQAr9/dBG9NSLTay/br37aL98px5oeNWgDSOoRbDZZaERj11jn2xJHTvVpy89+EunK7V5qazr1zde+a4dAqQ1/DxQBXD0ePHsVtt92G559/Ht999x1yc3MdvsaUKVMwduxYbN++HSUlJVCr1Th27BhefvllXH/99cjJcbzrnxoeSzs4yNGIgEoQzUKR+koNuOHXRWHxnVc3lHeUXNhSC8DX05th7vB4q+dNuCFK+qGkrz/XtXmo0Qb3ckRYnutHvk8MCHdqGNQVTo38w9NNIALAAFdvMTExSEtLw6xZs7B27VqHzn3nnXewYsUKqFQqLF26FGVlZSgtLcXu3bvRsmVL/P333xg7dqyLWk7+xNIiBjlqAejW0jgUGRYMNtxQ/s3xTRye86YVgeHXXu010y826No8FMOvi5Btp75sycLRidg9uxU+m9wU6bNaSatnx/WMRvos3fOzh8kvvNCXFCH/Z2kY1dIqVMMeK0PO9I65e7izPosgyL+xjEg9XHfddSgoKIAgON5VUV1djXnz5gEAZsyYgaeeekp67aabbsLXX3+N7t27Y/fu3Vi/fj1GjBihVLPJD5nu4GCJyiCoyRUMlisGPPnmGLy/q8ih9nz/p+4XjYCriw1iwtQY1zPaqJ0qAA/1i8EDfWKk1aSWauDpn7+xTRh6p4Ri1FvnWFLEz7i7/MY1666xuKOCUuS21DIdnmXxXnIGA1w9qFTOd2D+9NNPuHTpEgRBwJNPPmn2empqKgYPHowtW7bg008/ZYAjmwwD2fqMUqzeW2J2zOt3N8HtXSOlx4ZhSbYY8LpLWDGxCT5IN14FKrftlRy5XROU2HS+a/NQLL7T+S3HyPM8VSvNVq+bXG03Qwxb5C0Y4Dxk+/btAIAuXbqgadOmssfceuut2LJlC7Zt2+bOppEP0weyVvGBZjXc9HPcLJEtBiwCD/33AsZ0i8Q3v5demT8HPDs0DqfzamVDoiWGuyYosem8EkGQGh5nFxXUd2XqyTEnufMCKYpz4DzkyJEjAIDOnTtbPKZTp04AgMuXLyMvz3xrISJLkqIDjRYi2NNDpd/c3pQI4JvfS/Fw/xipHtuSTfloGedYYBLsHOLMLa41q1lniX5IleGNlOLcvDjjgruO9NL5+5Zh5DrsgfMQ/YrV5GTLW7cYvpabm4v4ePkVfNXV1aiurpYel5TY3ytC/kvJHiqNCLy9o8hoSHTJpnyzoVSp6K7MNUQRuFRSJ9uO3OJaZOXV4s9zVVjyQ77RHDy5bcCo4dGvRLW23ZV91+EQKPkHBjgPKS/Xza8IDZXfaBwAwsKu/qApKyuzeNyiRYvw0ksvKdc48huODFVa2twekN9IXjakAXhzQiJyizVY8L15r7Hc3qyGCyeMri8Cs9fq5s2xh41s7VWq1N6q+oDn6Bw90/c/MaHYZpuJ6qPBDaHOnz8fAQEBTt3mzJnj6ebLmj17NoqLi6Xb2bNnPd0k8kGWSpGoANk9U1Uwr/mmL1FiqVyI6d6slnaE0NMC+Ci9yMFPQkTk/xpcD5xWq4VGo3HqXGfPkxMervvrsLLS8hZAFRVX52JERERYPC44OBjBwcGKtY38l36oMkVmSNW0FIlKAB7qG4MH+upKfMSEqs1WfQKwuBJ00ZjGmL32kllPneFiBnsKEH+QXiS1gQhQpodNKa7uZfPUal3yfg0uwM2bN0+qv+ZJycnJOHTokNWdFgxfS0pKckezyI/J1XgznV9mbd6cpdesHd+hSRBGvX0OokFIM6zXpu/1sxbitAaBj0hpYkCY0dw6oa5CkaFY3bWvhi/DsiT6YsBE9dHghlC9hX6FaWZmpsVj9CtVExISLC5gILKHbI23tfJbT+nLkGTl1Zq9Lrfq09pK0K7NQ7HYwo4P+nNtbZOlsrB61ZHVquTfHOkFU7IHTlV12aneN6GugrsrUL01uB44bzFw4EAsW7YMmZmZyM3Nle1h27x5MwAgLS3N3c0jPyNb4w26+WXPDU8wet6enjo5loZnba2G1b/+/R9lsgsfHpIZPrXVRmtDxdRwyC1sUGo1q6Ms9cYROYs9cB6SlpaGxo0bQ6vV4tVXXzV7PSMjAz/99BMA4J577nF388jPWKrx9kF6kVEPllxPnT2bxH+xrxh9Fmdjworz6LM4G1/sMx4eslWvLSk6UHbhgwrAA31jjJ6z1UZbbSEyZVzHjWVGyDcwwNVTYWEh8vLypJteSUmJ0fO1tca/AIODg6W5eMuXL8err74q1XL79ddfMXr0aGi1WvTp0we333672z4P+aek6EBMvjnG7Hn9/DI9uZ46W5vEOxv65Nq4yGS4ddGd5sWHrbVRqbaQe3CjdiLncQi1nlJTU3H69Gmz58eNG2f0ePv27RgwYIDRc4888gh+//13rFixAk899RRmz56N4OBgqeZb69atsWbNGpe1nRqO3OJaXNc82KzwrukG8HKLCmxtEm8tUDk6fGlP8WFrbVSyLeRdfGE1prt2VVCq5h35NvbAedj777+PL774AgMHDkRERATq6urQoUMHzJkzB4cOHbK6UwORPfRDio+uvggA0lCq3PZacr1g9mzBJVcPzp5ts+TYM9xqqY1Kt4WIyFuxB66esrOz632NsWPHYuzYsfVvDJEJ0yFFEbpJ/2/c3QTdW4XIhiRHt+AyrR9nT+irL0tt9ERbiADdBvXWesIMe824mT0pgQGOyI/Jrj4VgbgItdVQ48gWXICy+67ay1IbPdEW8i3WhmN9YaiWCGCAI/Jrzsxpc5ajoc+VvKkt5HqeKg2iDUlwKuzJFfLlvDZyFOfAEfkxZ+a0EfkL4/IgDETkX9gDR+TnOKRIROR/GOCIGgBbQ4retHOBN7WFXIvzzYicxwBH1MA5u3WWv7eFfEtDCoMN6bOSZZwDR9SAedPOBd7UFiIib8ceOKIGzJt2LvCmthApjb1mpDT2wBE1YN60c4E3tYWIyNsxwBE1YN5UZsSb2kLkbix5Qo7iECqRj6vvqk1vKjPiTW0hIvJmDHBEPkypVZvetHOBN7WFiMhbcQiVyEdx1SYRUcPFAEfko6yt2iQiIv/GAEfko7hqk4io4WKAI/JRXLVJ/kqoK0e71dFotzoaQl25p5tD5JW4iIHIh3HVJhFRw8QAR+TjuGqTiKjh4RAqERERkY9hgCMiIiLyMQxwRERERD6GAY6IiIjIxzDAEREREfkYrkIlIiKvIgaE48SEYk83g8irsQeOiIiIyMcwwBERERH5GAY4IiIiIh/DAEdERETkYxjgiIiIiHwMAxwRERGRj2GAIyIiIvIxDHBEREREPoYBjoiIiMjHMMARERER+RgGOCIiIiIfwwBHRERE5GMY4IiIiIh8DAMcERERkY9hgCMiIiLyMQxwRERERD6GAY6IiIjIxwR4ugGkPFEUAQAlJWUebgkRuUJpaQlqa4M83QwiUlhZWQmAq7/HrWGA80OlpaUAgObN+3u4JUREROSo0tJSREdHWz1GEO2JeeRTtFotcnJyEBkZCUEQPN0cv1NSUoLmzZvj7NmziIqK8nRzqIHh9x95Er//XEsURZSWliI5ORkqlfVZbuyB80MqlQrNmjXzdDP8XlRUFH+Akcfw+488id9/rmOr502PixiIiIiIfAwDHBEREZGPYYAjclBwcDBefPFFBAcHe7op1ADx+488id9/3oOLGIiIiIh8DHvgiIiIiHwMAxwRERGRj2GAIyIiIvIxDHBEREREPoYBjsgO1dXV+PHHH7FgwQLccccdSE5OhiAIEAQBP/zwg93X+fLLLzFo0CDExcUhLCwMHTt2xNy5c6Xtz4gsuXDhAmbMmIE2bdogJCQEiYmJGDFiBLZu3erpppEPKy0txXfffYfnn38eQ4cORXx8vPSz7dixYzbP12q1eP/993HjjTciJiYGkZGRSE1NxdKlS1FTU+OGT9BwcRUqkR0OHTqE1NRU2dc2bdqE2267zeY1pkyZghUrVgAAAgICEBISgrKyMgBA69atsWvXLiQnJyvXaPIbf/zxBwYNGoT8/HwAuir4ZWVl0Gq1EAQBCxcuxKxZszzcSvJF33zzDUaPHi372tGjR9GhQweL59bW1mLUqFHYuHEjACAoKAhqtRqVlZUAgJ49e2Lbtm2IiIhQvuHEHjgie8XExCAtLQ2zZs3C2rVrHTr3nXfewYoVK6BSqbB06VKUlZWhtLQUu3fvRsuWLfH3339j7NixLmo5+bLKykqMHDkS+fn5SE1NxeHDh1FcXIzCwkI8+eSTEEURzz33HDZv3uzpppKPaty4MYYNG4YXX3wR77//vt3nzZ07Fxs3bkRISAhWrVqFiooKlJeXY/369WjUqBH27duHqVOnurDlDZxIRDZpNBpRq9UaPQdABCBu2rTJ6rlVVVVi48aNRQDiE088Yfb6wYMHRUEQRADid999p2i7yfctX75cBCBGRESI586dM3t91KhRIgCxW7duHmgd+bq6ujqjx1lZWdLPtqNHj1o8Lzc3VwwODhYBiK+99prZ6998840IQBQEQczIyFC83SSK7IEjsoNKpYIgCE6d+9NPP+HSpUsQBAFPPvmk2eupqakYPHgwAODTTz+tVzvJ/+i/JyZMmICmTZuavf70008DAA4ePIjjx4+7tW3k+9RqtVPnrV27FtXV1YiOjsaUKVPMXr/jjjvQrl07iKKI1atX17eZJIMBjsjFtm/fDgDo0qWL7C9gALj11lsBANu2bXNbu8j7lZaW4sCBAwCufo+Y6t27N6KjowGACxrIbfQ/1/r164eQkBDZY4YMGQKAP9dchQGOyMWOHDkCAOjcubPFYzp16gQAuHz5MvLy8tzSLvJ+R48ehXhlnZml7x+VSoX27dsDuPq9RuRqjvxcM/w+JuUwwBG5WG5uLgBYXWFq+Jr+eCLD7wV7vn/4vUPu4sjPtbKyMmnFPSmHAY7IxcrLywEAoaGhFo8JCwuT7vMHHenpv3cA+75/+L1D7sKfa57HAEd+a/78+QgICHDqNmfOHE83n4iIyKIATzeAyFW0Wi00Go1T5zp7npzw8HAAkIpbyqmoqJDus+gl6em/dwDd909kZKTscfrvH37vkLuEh4ejqKiIP9c8iD1w5LfmzZsHURSdui1evFixdujngeTk5Fg8xvC1pKQkxd6bfJvh/CJ7vn/4vUPu4sjPtYiICIt/fJDzGOCIXEy/EiszM9PiMfoVXQkJCYiPj3dLu8j7dejQQao/aOn7R6vVSvXf9N9rRK7myM+1jh07uqVNDQ0DHJGLDRw4EIDuB52lVYL6bZDS0tLc1i7yfpGRkejRowcAYMuWLbLH7NmzB8XFxQD4/UPuo/+5tmvXLlRVVckeo/+e5felazDAEblYWloaGjduDK1Wi1dffdXs9YyMDPz0008AgHvuucfdzSMvN2HCBAC6HRnk/gBYtmwZAKB79+5SPTgiVxszZgyCg4NRVFSEDz74wOz19evX4/jx4xAEAePHj/dAC/0fAxyRnQoLC5GXlyfd9EpKSoyer62tNTovODgY8+bNAwAsX74cr776KqqrqwEAv/76K0aPHg2tVos+ffrg9ttvd9vnId8wdepUtGzZEqWlpbj99tulYanS0lI888wzWLduHQBg4cKFnmwm+TDDn1+FhYXS80VFRUavabVa6bUmTZpgxowZAIBnnnkGH3/8sbT4a+PGjXjggQcAAOPHj8d1113nxk/TcAgiyyMT2aVVq1Y4ffq0zeO2b9+OAQMGmD0/ZcoUrFixAgAQGBiI4OBgqTZS69atsWvXLqtFManhysjIQFpaGvLz8wEAUVFRKCsrg1arhSAIWLhwIWbNmuXhVpKvsnef56ysLLRq1Up6XFtbi1GjRmHjxo0AdH+sqtVqafVpz549sXXrVi5gcBH2wBG5yfvvv48vvvgCAwcOREREBOrq6tChQwfMmTMHhw4dYngji7p27YrDhw/j8ccfR+vWrVFdXY24uDgMHz4cW7ZsYXgjjwgMDMT69evx7rvvonfv3ggODoYgCLj++uuxZMkSpKenM7y5EHvgiIiIiHwMe+CIiIiIfAwDHBEREZGPYYAjIiIi8jEMcEREREQ+hgGOiIiIyMcwwBERERH5GAY4IiIiIh/DAEdERETkYxjgiIiIiHwMAxwRERGRj2GAIyIiIvIxDHBEREREPoYBjohktWrVCoIg1Os2c+ZMT38MIiK/xABHRFQP2dnZRqH1n//8p6ebREQNAAMcERERkY8J8HQDiMg3LFu2DF27dnXonBYtWrioNUREDRsDHBHZpXv37hgwYICnm0FEROAQKhEREZHPYYAjIiIi8jEcQiUir3H8+HFkZGTg8uXLKC4uRqNGjZCcnIy+ffuiUaNG9b5+VlYWMjMzcebMGRQXFyMgIACNGjVCy5Yt0bt3b0RERCjwKXzX4cOHcfToUeTm5qKsrAyJiYmYOHEiAgMDbZ7r6q8dEZkQiYhktGzZUgQg3bZv3+6S9yktLRXnzZsnpqSkGL2f4U2tVosDBgwQd+7c6dC1Kysrxa+++kqcMGGC2KRJE4vX17/HkCFD7P6cpv8+9t4++ugjo+u8+OKLTv87Z2VlGZ17//33Wzx2+/btRse++OKLoiiKYm1trfj666+LnTt3lm1vYWGhxWu68mvnjCeeeMLovW+77Ta7zz1z5ozYrFkzo/Ofe+45F7aWqH44hEpEHrNhwwa0adMG8+bNQ1ZWlsXjNBoNduzYgX79+mHq1Kmoq6uz6/p9+/bFXXfdhdWrV+PChQtWj9VoNNi8eTMGDhyIRx991O738GWFhYUYOHAgHn/8cWRmZjp0rqu/ds6YM2cOoqOjpcc//PADdu3aZfO8vLw8DBkyBOfOnZOee/jhh/Hyyy+7pJ1ESmCAIyKPeP/99zFq1ChcunTJ6PmwsDB07NgRvXr1wjXXXAOVSmV23l133QVRFG2+R1VVldlzycnJ6NKlC3r37o1rr73W6Be+3ltvvYUpU6Y4+Il8S11dHUaOHIn09HTpudjYWFx33XW47rrrZP9d9NzxtXNGXFwcZs+ebfSc6WNTZWVlGDZsGI4dOyY9N27cOLz11lsuaSORYjzdBUhE3smVQ6g//fSTqFKpjK4/YsQIcceOHWJtba3Rsfn5+eKSJUvEyMhIo+MXL15s8306d+4stmjRQnzyySfFrVu3isXFxWbHaLVaMSMjQ3zkkUdEtVpt9B7r1q2zeO309HRxy5Yt4ieffGJ0zpAhQ8QtW7ZYvOXk5Bhdx1NDqImJidL9wYMHi7t37xY1Go3Rv8uWLVvEqqoqo+u462vnrMrKSrF58+ZG77dhwwbZY6urq8XBgwcbHXvrrbeKNTU1LmsfkVIY4IhIlmmAW7ZsmdVgYnorKCiQvW5hYaHRfDSVSiWuXLnSZnsyMzPFhIQE6bygoCAxNzfX6jk7d+4U6+rq7P7MmzdvFoODg6X36NWrl81zHAlRcjwV4PS3mTNn2v1+7vza1ceqVauMPuP1118varVao2M0Go34j3/8w+i4m266SSwvL3dZu4iUxABHRLKcnaRvK4gsWrTI6LhFixbZ3abvv//e6Nw5c+Yo9Gmvmjt3rtF7ZGZmWj3elwPcTTfdZBZsrPH2r52eRqMRu3btavR+n332mdExDz/8sNHr1157rdUFG0TehnPgiMhtNBoN3njjDelxixYt8OSTT9p9/rBhw5Camio9Xrt2raLtA4B7773X6PEvv/yi+Ht4i/nz50MQBLuO9YWvnZ5KpcKSJUuMnnvhhRekBRQvvPAC3n33Xem1Nm3aYPPmzYiJiXFZm4iUxgBHRG6TkZGBnJwc6fHdd99tV40xQ0OGDJHuHzt2DHl5eYq1DwBSUlKMHv/++++KXt9bJCYmYtCgQXYf7wtfO0O33norBg8eLD3+66+/8OGHH+KNN97A//3f/0nPJyUlYfPmzWjSpInL2kLkCizkS0R22b59e733QjUt6dCjRw+Hr9GiRQujx0ePHsXNN99s87y9e/fim2++waFDh3Ds2DEUFRWhtLTUZlkLV4YMT+rRo4fdvW+AZ792zlq6dCm6desmrXp99tlnUVxcLL0eGxuLH3/8Ea1bt7breiUlJfj999+xf/9+7N+/HwcOHMDJkyel62dlZaFVq1aKfw4iOQxwROQ2R48eNXo8duzYel+zoKDA6uu7du3Co48+ij/++MOp6xcVFTl1nrcz7Wm0xRNfu/q6/vrrcc899+CTTz4BYPy1DA8Px/fff49rr73W7uv1798fhw4dUriVRM7hECoRuU1+fr7i1zTsUTH13nvvoX///k6HNwCorq52+lxvFhUV5dDx7v7aKeXll182G+oNCgrCunXrcOONNzp0LdGgfl10dDQGDBjAoVfyGPbAEZHbuKI3S6vVyj6/fft2PPLII0a/dAMCAtC3b1/ccMMNaNmyJRo3boyQkBAEBwcbnXvLLbco3k5v4+j8NXd+7ZS0bt061NbWGj03ePBgo/l49po0aRISEhLQo0cPXHPNNRAEAQMGDLC5yweRKzDAEZHbhIWFGT1evHgxunfvXq9rdu7cWfb5J5980ii8DR8+HO+++y6aNWtm9Xr+2uNWX+782inlf//7H/71r3+ZPb9p0yYcOHDA4fY//vjjSjWNqN4Y4IjIbeLj440ep6SkGK0UVMqJEyeMVo926dIF69atQ1BQkM1zXT0vy5QjCwlMVVRUKNgS69z1tVPKd999hwcffFAK8SqVSurxE0URzzzzDLZu3erJJhLVC+fAEZHbmE6cP3nypEve57fffjN6/NBDD9kV3gA4vKl7fYWEhBg9rqystPvcy5cvK90ci9z1tVPCzz//jHHjxkkrjAMDA7FhwwZ06tRJOmbbtm3YuHGjp5pIVG8McETkNgMHDjR6vG3bNpe8z8WLF40et2/f3u5zHW2T6YbtooMbtZsuJjBtuzX79u1z6L3qw11fu/o6ePAgRo4ciaqqKgC6r8///vc/DB06FAsWLDA69tlnn3XLPDwiV2CAIyK36dWrF2JjY6XH27Ztw5EjRxR/H9MQVVNTY9d51dXV+PDDDx16r/DwcKPHjg5rtmzZ0uixI4WDv/jiC4feqz7c9bWrjxMnTuC2225DSUmJ9Nzrr7+Ou+++GwAwevRo9OrVS3rt8OHDWLVqlbubSaQIBjgicpvAwEDMnDlTeiyKIqZOnWq2SrC+TEs7pKen23Xe888/71APGKDrQVOr1dLjrKwsh87v1q2b0eOvv/7aZnFhQLe6cv/+/Q69V32462vnrHPnzuGWW24xGlaeN28epk+fbnTcwoULjR6/8MILDg1bE3kLBjgicqsZM2YgMTFRepyeno677rrLoZpg5eXleP3117Fy5UrZ12+66Sajx++++67NOVvvvfceli1bZncb9AIDA9GuXTvp8aFDh3Dq1Cm7z2/SpInRHqFnz57FK6+8YvWcffv24aGHHnK4rfXljq+dM/Lz8zFkyBCcOXNGem769Ol48cUXzY5NS0tDWlqa9Pj8+fNYvny5Ym0hchcGOCJyq+joaHz55ZdGdci+++47dO7cGa+++qrRL2FDZ8+exVdffYV7770XycnJmDFjBs6ePSt77DXXXGNUpLW0tBT9+vXDl19+ada7lZGRgXHjxuHhhx+GKIro2LGjw5/JsKaYRqNBv3798NJLL+Hrr7/Gli1b8NNPP0m33Nxcs/MnT55s9Hju3LmYPXs2CgsLjZ7PycnBiy++iP79+6OwsBBt2rRxuK314Y6vnaPKysowdOhQo50i7r77brz++usWzzHthVuyZInfbplGfkwkIpLRsmVLEYB02759u6LX/+yzz8SQkBCj99DfkpKSxK5du4q9evUS27dvL8bGxsoe9+KLL1q8/u7du8XAwECzcyIiIsTU1FSxe/fuYmJiotFr4eHh4sGDB42e69+/v83Pcvz4cYufxfT20UcfmZ1fW1srpqammh0bEBAgdurUSezVq5eYkpJi9FqTJk3EHTt2GD13//33W2zj9u3b7f63s8XVXzt7VVVViWlpaUbXvfXWW8Wamhqb544ePdrovMcee8ypNvTv31+6RlZWllPXIHIGe+CIyCPuvvtupKenGw0/6uXm5iIjIwN79+7F8ePHzXqiAECtViM5Odni9W+66SasWLHCbMeBsrIy/P777zhw4IDRfLfY2Fhs2LDBaDjTXu3atcPHH3+MiIgIh88FdDtErFu3zqxHra6uDkeOHMHevXuN5ta1aNECP/30k9kCCHdx9dfOHhqNBuPHjzeq5XbDDTdg7dq1du0ysWDBAqMVxO+++65DQ99EnsYAR0Qe0717dxw5cgT/+9//0Lt3b6PFAHKCg4MxaNAgLFu2DGfPnsWUKVOsHn///fdj586d6Nevn8VjQkJCMGnSJGRmZmLAgAHOfAwAwF133YUTJ05g8eLFuPXWW9G8eXNERETYXai3VatW2LNnD6ZNm2a2tZdeaGgoHnvsMWRkZLh8FwNbXP21s2Xq1Kn4+uuvpccdO3bExo0bzVYFW9KpUyfcd9990uPa2lrMnj27Xm0icidBFB0sWkRE5CLFxcX47bffkJOTg7y8PNTW1iIyMhKNGzdGhw4d0L59e7PCt/bKzs7G7t27kZubi+rqasTExKB9+/a46aabzLaJ8rTy8nL8/PPPyMrKQlFREcLCwtChQwf069fP7oDibq782nmzAQMG4OeffwagW4HcqlUrzzaIGgwGOCIiIicxwJGncAiViIiIyMdwM3siIiI7nDx50qwo9IULF6T7X331FeLj46XHERERuOuuu9zWPmpYOIRKRERkh1WrVuGBBx6w+/iWLVsiOzvbdQ2iBo1DqEREREQ+hj1wRERERD6GPXBEREREPoYBjoiIiMjHMMARERER+RgGOCIiIiIfwwBHRERE5GMY4IiIiIh8DAMcERERkY9hgCMiIiLyMQxwRERERD6GAY6IiIjIxzDAEREREfmY/wcKTz20MNKWuQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "from matplotlib.collections import PatchCollection\n",
    "from matplotlib.patches import Polygon\n",
    "from sklearn.datasets import make_blobs\n",
    "\n",
    "centers = [(-5, 10), (5, 10),\n",
    "           (5 * 1.67 + 2.5, -5 + 2.5 * 1.67), (5 * 1.67 - 2.5, -5 - 2.5 * 1.67), \n",
    "           (-5 * 1.67 + 2.5, -5 - 2.5 * 1.67), (-5 * 1.67 - 2.5, -5 + 2.5 * 1.67)]\n",
    "n_samples_per_cluster = 100\n",
    "\n",
    "X_0 = X_1 = np.ndarray((0, 2), dtype='float')\n",
    "y_0 = y_1 = np.array([])\n",
    "for i in range(3):\n",
    "    X_temp_0, y_temp_0 = make_blobs(n_samples=n_samples_per_cluster, centers=centers[2 * i: 2 * i + 1], shuffle=False)\n",
    "    X_0 = np.concatenate((X_0, X_temp_0))\n",
    "    y_0 = np.concatenate((y_0, np.full(n_samples_per_cluster, 0)))\n",
    "    X_temp_1, y_temp_1 = make_blobs(n_samples=n_samples_per_cluster, centers=centers[2 * i + 1: 2 * i + 2], shuffle=False)\n",
    "    X_1 = np.concatenate((X_1, X_temp_1))\n",
    "    y_1 = np.concatenate((y_1, np.full(n_samples_per_cluster, 1)))\n",
    "    if i == 0:\n",
    "        X_red = np.concatenate((X_temp_0, X_temp_1))\n",
    "        y_red = np.concatenate((np.full(n_samples_per_cluster, 0), np.full(n_samples_per_cluster, 1)))\n",
    "    elif i == 1:\n",
    "        X_yellow = np.concatenate((X_temp_0, X_temp_1))\n",
    "        y_yellow = np.concatenate((np.full(n_samples_per_cluster, 0), np.full(n_samples_per_cluster, 1)))\n",
    "    else:\n",
    "        X_blue = np.concatenate((X_temp_0, X_temp_1))\n",
    "        y_blue = np.concatenate((np.full(n_samples_per_cluster, 0), np.full(n_samples_per_cluster, 1)))\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "region_red = Polygon(np.array([[0, 0], [-25, 15], [25, 15]]), closed=True)\n",
    "region_yellow = Polygon(np.array([[0, 0], [-25, 15], [0, -100]]), closed=True)\n",
    "region_blue = Polygon(np.array([[0, 0], [25, 15], [0, -100]]), closed=True)\n",
    "patches = [region_red, region_yellow, region_blue]\n",
    "p = PatchCollection(patches, alpha=0.15)\n",
    "p.set(facecolor=['red', 'yellow', 'blue'])\n",
    "ax.add_collection(p)\n",
    "\n",
    "ax.scatter(X_0[:, 0], X_0[:, 1], marker='.', label='Class 0')\n",
    "ax.scatter(X_1[:, 0], X_1[:, 1], marker='|', label='Class 1')\n",
    "\n",
    "ax.set_xlabel(r'Feature $x_1$', fontsize=30)\n",
    "ax.set_ylabel(r'Feature $x_2$', fontsize=30)\n",
    "ax.set_xlim(left=-15.5, right=15.5)\n",
    "ax.set_ylim(bottom=-14, top=14)\n",
    "ax.legend(facecolor='white', framealpha=0.7, fontsize='xx-large', loc='center')\n",
    "ax.tick_params(axis='both', labelsize='xx-large')\n",
    "\n",
    "plt.show()\n",
    "PATH_TO_IMAGES = \"./images/data_similarity/\"\n",
    "if not os.path.isdir(PATH_TO_IMAGES):\n",
    "    os.makedirs(PATH_TO_IMAGES)\n",
    "fig.savefig(os.path.join(PATH_TO_IMAGES, \"synthetic_dataset_visualization.png\"), dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "656d1e88",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_red_train, X_red_test, y_red_train, y_red_test = train_test_split(X_red, y_red, test_size=0.3, shuffle=True)\n",
    "X_red_train, X_redd_train, y_red_train, y_redd_train = train_test_split(X_red_train, y_red_train, test_size=0.5, shuffle=True)\n",
    "X_yellow_train, X_yellow_test, y_yellow_train, y_yellow_test = train_test_split(X_yellow, y_yellow, test_size=0.3, shuffle=True)\n",
    "X_blue_train, X_blue_test, y_blue_train, y_blue_test = train_test_split(X_blue, y_blue, test_size=0.3, shuffle=True)\n",
    "X_test = np.concatenate((X_red_test, X_yellow_test, X_blue_test))\n",
    "y_test = np.concatenate((y_red_test, y_yellow_test, y_blue_test))\n",
    "RED = (X_red_train, y_red_train)\n",
    "REDD = (X_redd_train, y_redd_train)\n",
    "YELLOW = (X_yellow_train, y_yellow_train)\n",
    "BLUE = (X_blue_train, y_blue_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b7b7320a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from derdava.data_valuation import ValuableModel\n",
    "from derdava.model_utility import IClassificationModel, model_knn\n",
    "\n",
    "data_sources = {0: RED, 1: REDD, 2: YELLOW, 3: BLUE}\n",
    "model_utility_function = IClassificationModel(model_knn, data_sources, X_test, y_test)\n",
    "\n",
    "valuable_model = ValuableModel((0, 1, 2, 3), model_utility_function)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a60d1623",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9945466883852736\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9962335102054991\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0026468609819903\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0004712018574828\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0008384295441937\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0007015425656491\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003478115924147\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0004489045536582\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004272245975694\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003846108716237\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0005652016535689\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0005405838588661\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0008417325033152\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0006248686130494\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0008978534154793\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0006277464088174\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0002438775426612\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0005104038180814\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0009461245526996\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0003654270950195\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9932142808241086\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9959826009629644\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9995432624804141\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9990201312332514\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0004799176798145\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0004300022629795\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002073604094612\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003682341499989\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998929040034903\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996604045292818\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9960907678413646\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0018152929736739\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0025293487270512\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0007270078050503\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0000536392396626\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000846518929635\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0001377222233825\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.00048752298099\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0008707503814207\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000579298525207\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.000432963572432\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000177725094834\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0002911192892736\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9886602136781414\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000124049831213\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9997775908974834\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.001103052532506\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999667838347523\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995268588086385\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998979611636454\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9993578292477974\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998047951316201\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0006613567818612\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999539847444451\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995030816433143\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996923416767424\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998402669681444\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997839366906829\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999034766509007\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9998651884095462\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0001303636375602\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0000813236512411\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0004994013133932\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0003189040684473\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0000692425150697\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9999479995119035\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9999150236519252\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9901620518908401\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9985549424640778\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9996628013937062\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0033773958099366\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.003295519245694\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0033971753686428\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0031354268853412\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0012901896472122\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.001289024319255\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0016641565594675\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.001145844442044\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0006773889739937\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0010918048875248\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0011475349626497\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0009804704124479\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0007735986607316\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0010894784179545\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.000421048807223\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0001790077417414\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.000559684998799\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0006417201731796\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0006040855913647\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.000791101383555\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000330504694703\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0004571623023633\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.000488676772585\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.0003082692174656\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 1.0005878710175757\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 1.0005546828703125\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 15000 - Average convergence rate = 1.0005443840947033\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 15500 - Average convergence rate = 1.0003871437700806\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 16000 - Average convergence rate = 1.0003333578266294\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 16500 - Average convergence rate = 1.0004261097142102\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 17000 - Average convergence rate = 1.00026451690356\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 17500 - Average convergence rate = 1.0002892784116655\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 18000 - Average convergence rate = 1.000227728378932\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 18500 - Average convergence rate = 1.0003720168516628\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9949031334081367\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9955882964632934\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9976484991826038\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.998665499871256\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9983944656096392\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9984240878032766\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9989847364789417\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9986678718596929\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995189021781998\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995240438959275\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9989330130385894\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9992397278853496\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997144706087306\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9993321313708678\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9994947054946268\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9994168892240958\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9994476473232646\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995189725640535\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9993723254554863\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9994774210988095\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9996271478363503\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9995682048118264\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9996422210432514\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9996378092326256\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.9996700536930485\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 0.9996238750646967\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0026255948686542\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000104858293967\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0001855822712695\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992643795799508\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9988617707126238\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9990411713250066\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993849933475443\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.99935223504052\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994700309900879\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9937399554728077\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9998886196010809\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0019415679805557\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0026365863627387\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0012888031297638\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0004188232618425\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0004096112303626\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9997057898563181\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9999386910186807\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000328931900897\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999441944767755\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998000070049646\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0101653607361651\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0045278734122953\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0028904640058083\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9994944829614092\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0006048839050066\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0029030257547817\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0001532148929972\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000150908110644\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0007952406597362\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0012744412881294\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0010254665703529\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0005312201341945\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0006413070949352\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0003579442477095\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000725443358918\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000784915308026\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000628774876726\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0004891897128085\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9909121174143442\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9962907113372299\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000108337641587\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.998812445385059\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0002961089249192\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9989497583653808\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0006185131699254\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003163251399854\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9934505720941447\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9976393715113263\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9988723129313696\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992052124752121\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9987540918124753\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000032651040058\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9992668822426821\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9997480193795211\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999592814227323\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994884427725688\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9994286584057667\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997589485453104\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995141925456935\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997387771006878\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996672739948287\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9994964398806917\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9926897547771589\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9947227435699207\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.99867694473754\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992089987179931\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0001356920527442\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0000590170818886\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0014213373052727\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0007204011802138\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0010349244865115\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000765288228536\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003757031850071\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000652738871305\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0006525087863771\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999086306622513\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9957641159886883\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0046306955382995\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0017290825412768\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.002745620416697\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0009402009480175\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999258017759399\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.999483271500113\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0007997366111767\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9993846552893837\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9991645102421384\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0002377912367584\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.004763735247889\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9993638356688189\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0004821601551441\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9989681645246463\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9997246367328001\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991652640378378\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9997828828106408\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9995034322365318\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994096320304072\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996876727335967\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998506056017428\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999495149751549\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9999387198577214\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996701297794868\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9987619840473833\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0019908360403438\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9990367932947795\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0006331000920827\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.000283093255592\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991676044486149\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002952037709194\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.001949076057087\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.001353386578237\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000961932178448\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0006738603866898\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0014824794771164\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0004824029628916\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0006583886582918\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0004968328795976\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0003826637400668\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9974643152814335\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0000549238662448\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993230437380982\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0004884036567767\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999705969285221\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995541527098417\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998931741072481\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9993042461050223\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996763596436586\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999838271945104\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003333820754865\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996432243413388\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0001707816967107\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0001404629377877\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999257770007036\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997043436980335\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9999654773979036\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9981267379207432\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9993219884317973\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.99761335523907\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9991243923630149\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9997382807273525\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9986779676963096\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9991729590920829\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999199498995899\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9963941908538171\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9996352375275268\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9988020824650274\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992861873028354\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9997737832692905\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995217275811548\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003983870821351\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0004001510897518\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0005402685726947\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003740562707555\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0002119634716644\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001375388665916\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997713907091961\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0074974551960092\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0010549244717586\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0012833232483547\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0007324465800438\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992934780009888\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995318051567447\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993968135871424\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9998269910591961\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0000493055896094\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996730945443467\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998844102393982\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9946490050156587\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0002123506619252\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000019374639737\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0017816717296928\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0005891397653\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0001115957524482\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9976688308381768\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9989471507492462\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.002230446851298\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.000167975299144\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999276496317511\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9989245657839422\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9992453239909802\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999571411680019\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994106555275373\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995517040285483\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0005810352323823\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997389282782128\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9933942713102565\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9995977834126413\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9987310448452474\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0009395978516142\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0006120462333936\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999600288653612\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002221902798354\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000370454933678\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995939916777387\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997962806279387\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996156674131422\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0016286785534376\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.006355522094999\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.003436795811731\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0046228990466046\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0012012824734495\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0005205016132221\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002699454417456\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0007271086580851\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.00065782524087\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003800553671438\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0002179631024049\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9999829929901742\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9947755666157809\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0011906716673875\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0029245687036588\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0021600845925374\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0002549898339832\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9997060185396922\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993141938792999\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.001470536079341\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0012742691905467\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0004804052050495\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0004047304091583\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0002960368014375\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000046778643295\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0004525915820337\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0002222993731245\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000181263942536\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0001725926202658\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.000223601460899\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0057672252622067\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0043341790296227\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.002939827867466\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0000474962329786\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0001746468454376\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994826686433216\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994104477104863\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0005007342120442\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004136304024258\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9999308738118511\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0002605826579978\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0005277096617236\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0005244057989722\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0001006697960806\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0014349155442308\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.002235461810848\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0003957038811224\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0013541742672676\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0009996670661439\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0008555011275926\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0005078763914426\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000574408243911\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0001792226651804\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0012206843050746\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999750045599396\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0004937252557933\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0003011225068597\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0002089047801777\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9998993391227512\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9997724002615337\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9998180043442197\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0001203146727253\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0003910871917532\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0000743872431792\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9999528336405853\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9999410576521972\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0000956051201175\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.000099496130866\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 0.9999891909230061\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9946821357527014\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000639149348583\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9984842263597224\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9994433855926282\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9986655384802852\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0000044678817128\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9995511490539837\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9996897931625947\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9993542063102446\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.99935684168417\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995223895911804\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.000907965033706\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0014730196220876\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0007609357432095\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9997410222283142\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0015196560937065\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999022360238893\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9990302786894187\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994685384826059\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997470835988457\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9999661657853605\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995137713775104\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9992385677290444\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999960481632445\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998543886942122\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999719837223658\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9998909717373672\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995074156125957\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9999767125863914\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.996770972958263\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9998768885764592\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0017827391732939\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0002451661087637\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0021473118315096\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0018847260455317\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.002007471480828\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0010851583794427\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0013534590654876\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0009977010952318\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0015018415472465\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.001467616844166\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9942138582839394\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0014466886170026\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9997181085428807\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.999536425560416\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9996298135331835\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0007011968938815\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998339793610531\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9995709962936778\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995544489822986\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9951461186726832\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9996816408223121\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0006404513356115\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9998258121600799\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992651838257248\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9981627108254758\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.00047611539935\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999174370722584\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998053303906927\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9993045885639795\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999080234327848\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999957437419091\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998171853596116\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0000195466444068\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.99956990631623\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0006043035797307\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9995797663829964\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.000221193345523\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0003336203826794\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992990277053211\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003386023347653\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0001588401733406\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996643134362249\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996648733131717\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998112847643874\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995649377238635\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996938579249044\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994468574672848\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999382569671684\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0003182104942447\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0076975517121967\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.003394120660682\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0014568828641337\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9990863240938502\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0004821082852617\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9999150419510998\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9990820078042267\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9991119161895056\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999995421406805\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.99955345976088\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997005583017096\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995725810954703\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996663089205489\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997633730777868\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0002031256863906\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0000628605882067\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000169746975995\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0003651793679458\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9999099977678605\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.000052911027904\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.000196811455343\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9947982574959167\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.003373157385362\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0004979198882213\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9999211857256813\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999474506712782\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995959374757959\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9995062033880482\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992309038739102\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0000781418379008\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999436250750922\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999652543376748\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000572358822364\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9929108022702156\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9945858101083596\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.997413258050758\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9984411998442334\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9991890717537865\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9986203492040242\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9997954307406227\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9958808387844922\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9957800166591726\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.001352244640398\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9994585699888183\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0022339512905192\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0014005768202217\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994515885201396\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9996811352742108\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994233750275332\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0007776630837741\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0007424985909408\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0004145666198272\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000239211567302\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0073963652435205\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0012698034681407\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9982605457354536\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0003146173290958\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0010251909151135\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991704257761578\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9992288774587822\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9987760593701251\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996196192147345\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994461962286755\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995599801537196\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9994305481373492\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997489730012844\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996672169270886\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997443420338236\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9949269165696635\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9985161371417011\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0011191784366769\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0019989495192765\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9989737500480474\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995209780796969\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998525346987008\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0007408305490837\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0062448448656591\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0000365782498974\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.001209116947642\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9988659950272545\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0012431965651607\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994988325087824\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003465281359785\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9997901564847567\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0000455069839704\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9999718570974746\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999050457822923\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9994753807850207\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000738957883597\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996843602144025\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0003466093035804\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9993543806845171\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.995940406272639\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9994727667987173\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9998600213557334\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992567480015793\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995458897724342\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998082337759159\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.00132784408085\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0021182808962044\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0018229140778492\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0009514932776291\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000595107135171\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.001174869506252\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000308700908657\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0051691317190214\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9973820375367419\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0016857395253091\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0005212619247095\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0001030117445817\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0015272024715283\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0001902228101287\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999548256213966\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0001062280313708\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9950955536429839\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9954179636323134\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9976419658811472\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9985450256963041\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999961240692964\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9996126924483316\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993530766553942\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999992642032318\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994671039343616\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000358195457213\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0004491370266924\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0004161302057781\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0002849760788242\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995516562630634\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000124720466036\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000063396757326\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0001999234391437\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0003573763188789\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0005378456552259\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0004502147169378\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0001048973381577\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0003432657486473\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0003104492064514\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000301194682124\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0003788737111963\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0002969181745376\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.000308054401677\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 1.000056411063918\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 1.0001964335546087\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9936994475980785\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0006660762038475\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000014362240269\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.001246182886372\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.001471938674693\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999118248695456\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.00027239971431\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0001004045743849\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004924074416341\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000818304589645\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.000414780636104\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0014631062733756\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0001126047121534\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0004634301479818\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000964715829175\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0004416768132842\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0008063271608338\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.000723520552322\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.000446210659726\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0005189983683191\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0003788928691968\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0003871373976554\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0004598589270168\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.0003369980251775\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0000523921166373\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0003172462930836\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.000996207917288\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 1.0000727769896354\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 1.0000581528044594\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9930806472480135\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9986419248728566\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9985759361718047\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9987775189508608\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9986442364571415\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999543270286594\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994974704355363\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9991080259862191\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9989757595161308\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9992160744544043\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996894737101893\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9994524485673166\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998248345417609\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995173002239541\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9992917639707537\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9995099852395999\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995295148567371\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995092688664367\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9982255344914218\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0032694933043926\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0029188059711827\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.001893170726806\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0009302621345866\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0005688498075709\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0011708466027753\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0006830605621526\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.001187890068437\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997816874230736\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9985714959182983\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0022904262631576\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0020845573207744\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0021942881023307\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.001747296765363\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0015830155297727\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998138852230235\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0015221790650193\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0017901823402853\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0010119818473973\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0013116524891092\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0007702063345356\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0007948684291494\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999880093534673\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0008896190110057\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0000741140909557\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0004251995077742\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.000415888567682\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.999857173804141\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.000176308581257\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0002660538264367\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0001657285321992\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0001949249955764\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000388415805965\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0049563565264306\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.999810400563301\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993259456138809\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0005900263837224\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0004127082877743\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995174759953717\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9989225468029315\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9989804756220926\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0003325914066088\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000535878752434\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9994028012086168\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998190805937064\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000284654853018\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0000407731754783\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.004870053755642\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0028922540625331\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.002900139824544\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0002659056164964\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9986264202864383\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9993592556803259\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9986833786910703\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999531142963323\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998230027070316\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994858868495748\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999465007709515\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997320367996885\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995849383558346\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995330210771294\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999960733920046\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999395364416244\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997689419038913\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0036968372020236\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9978422021918891\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9987966161552844\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9994525896056379\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992836710632349\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991506229704036\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9997346098573174\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9995006721118551\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9999898232115765\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0005287060928532\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999844278056345\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997207678140803\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000752572974907\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0001858303603681\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0002904682468245\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9998581007733987\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0000729091111653\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0003082209076213\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.000232656473852\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.000336652512111\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0001965964225354\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0004695259461565\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0005947464210188\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000250844743916\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0103056657468452\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9984955010310326\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0018212804229056\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992410055267595\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9991234429358152\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992273700003858\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994876771862776\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9997476300789419\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997576557230423\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996846257974423\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995244109033494\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.998623783008335\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9975046057098976\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9963982956065308\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9981770820829516\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.000011370922002\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998133294832574\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0049895529549682\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9997869816715002\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9987430111355059\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9976292902040371\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9979255497886916\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9984200083573562\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9984519234976592\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994944576336953\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997613224079193\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0019214030994876\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0024740725738692\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.998175770404476\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.998242889719171\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9984993716528553\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9989199841038694\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9991567442947455\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.99892936271353\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.99914442408387\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9992342721630545\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999437321589812\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995049824263382\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996329190110304\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997828757471023\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9995511081807975\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9925112764438205\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9993130149191861\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.999930791829941\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9987270558663951\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9995813544047554\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992845992702692\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9989065540882506\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999786797415622\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9989131169961456\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999535346310659\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999301369975016\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995329496466493\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9994833536489105\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996825718179383\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999767870561267\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000480228826181\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0000093892169175\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0008724469874135\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9998718040801304\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.995705489117114\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9997552276443156\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0002589087262606\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0009746212750779\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0007896163170837\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0003437180302612\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003732856898584\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9998667760806151\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0001502616435316\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9993981875928868\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998481427648386\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001595191660335\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999846683211081\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.00082932407733\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9992812508210728\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9985753507874762\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9979153560711458\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9987199128370634\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9990546941510817\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9990429190182679\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992492168216616\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9989553960742573\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9992089386706181\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999327060944505\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999734621043739\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999796531737979\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000137745977756\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998185499417929\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0005975177394808\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9976143479413677\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000311252541434\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.999357757157219\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999350622877388\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9990755565661505\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9988631101171196\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9993742205436013\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9992016832539679\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9992648362671537\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9990059706134203\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9991647724514048\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999597047057917\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9992121801273937\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9993728276847068\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9994515553045376\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995151564839052\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9994937209926044\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9996802835590585\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.005080969061074\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0044990444245205\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0004464143006713\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9993657901673492\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9989606090178067\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9997387863083924\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9988562775814684\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9990317878957053\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9991954566452484\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998636021093154\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995990040230938\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996213019424065\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9999669822293746\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998686786657698\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996363557543927\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000096310850507\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0013146135684265\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9999727902987856\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000389015599159\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9994090247268619\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9984910199084525\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.999619397501271\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9987878293501466\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9988704417098381\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9989797435941957\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9988253219705073\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9989095940357107\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9991889927649841\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995628742367855\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9991385821126957\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9994594916718493\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9993676783469313\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9993879271581143\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9996306296453413\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9996108444814469\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9926702236567455\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9989070802314004\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0007478982652676\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9988633185733622\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0005631171333376\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0006951926991938\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.999010192599493\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999822431701411\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996715391610814\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996318880863124\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0005007410620745\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999467728631592\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999804272779157\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996650368419608\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 4\n"
     ]
    }
   ],
   "source": [
    "from derdava.coalition_probability import IndependentCoalitionProbability\n",
    "\n",
    "x = [[] for i in range(6)]\n",
    "y = [[] for i in range(6)]\n",
    "\n",
    "for i in range(4): # 100%, 67%, 33%, 0%\n",
    "    x[i] = [1 - 0.05 * j for j in range(21)]\n",
    "    for j in range(21): # 100%, 95%, ..., 5%, 0%\n",
    "        coalition_probability = IndependentCoalitionProbability({0: 1 - 0.05 * j, 1: 1 - 1/3 * i, \n",
    "                                                                 2: 1 - 1/3 * i, 3: 1 - 1/3 * i})\n",
    "        y[i].append(valuable_model.valuate(data_valuation_function='012-mcmc robust banzhaf', \n",
    "                                           coalition_probability=coalition_probability, tolerance=1.0005)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f34dbe84",
   "metadata": {},
   "outputs": [],
   "source": [
    "banzhaf_score = valuable_model.valuate(data_valuation_function='banzhaf')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4e5417e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x[0], [banzhaf_score] * 21, linestyle='dashed', color='gray', label='Banzhaf')\n",
    "for i in range(4):\n",
    "    ax.plot(x[i], y[i], color='C' + str(i), label=f'{round((1 - 1/3 * i)*100)}% stay')\n",
    "    \n",
    "ax.set_xlabel(r'Staying prob of $\\mathtt{RED}$', fontsize=30)\n",
    "ax.set_ylabel('Valuation score', fontsize=30)\n",
    "ax.legend(facecolor='white', framealpha=1, fontsize='xx-large', loc='upper right')\n",
    "ax.tick_params(axis='both', labelsize='xx-large')\n",
    "plt.gca().invert_xaxis()\n",
    "PATH_TO_IMAGES = \"./images/data_similarity/\"\n",
    "if not os.path.isdir(PATH_TO_IMAGES):\n",
    "    os.makedirs(PATH_TO_IMAGES)\n",
    "fig.savefig(os.path.join(PATH_TO_IMAGES, \"synthetic_dataset_result.png\"), dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec4e8550",
   "metadata": {},
   "source": [
    "## Actual Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7633ee99",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0023195213230671\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9981225815637598\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9987036416716735\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9988744319336919\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999685763829596\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.99913829625537\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994695512064441\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9993580137322627\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9990902436563222\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9991526903976361\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999539649907433\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998971647401348\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998408642818092\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997883957389484\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9995021896662907\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999206722555699\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.999740581545888\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9997213051426587\n",
      "---------> Number of values that have not converged: 3\n",
      "0 0\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.996911329590036\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9987095973885056\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0000035051108955\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0006022480654544\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9998075200067538\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0003886073417922\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0012171634884728\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.001094570387801\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0007894035980054\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000461349662676\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000097390685958\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000019630259201\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000077259505125\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998844672092887\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000081224557501\n",
      "---------> Number of values that have not converged: 1\n",
      "0 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0017736525919663\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0015166361838708\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993153244431167\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0006971337977688\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992176500610852\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992945492041061\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.999991333096436\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0000975128158711\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996097630099787\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997922060023239\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0004310309415054\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996579145763347\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0001537226474158\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000101238919055\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999512153973086\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000258940589578\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0000230564174069\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.999712812098839\n",
      "---------> Number of values that have not converged: 1\n",
      "0 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0256547385141639\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0091963647385331\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.005731910700913\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0015473906062213\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0015256606344385\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0005885616257724\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002303189098296\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9995221092862955\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995042449154093\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998850085097363\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9993589581064614\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9993995399983905\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995038622873893\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994365480681808\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996343097959843\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9993790370374823\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995672920679893\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9996208278447719\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9997441653423825\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9994656909060123\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9997364479874742\n",
      "---------> Number of values that have not converged: 1\n",
      "0 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9978736305323633\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9986408469267496\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9981194322407833\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992762727434824\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9990948338513744\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991699100998859\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.999477136563562\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9990927329584807\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997679826495874\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.99982012339699\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9993449237846282\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996851869251994\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998741853299511\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998202755599074\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997922830046856\n",
      "---------> Number of values that have not converged: 2\n",
      "0 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0025652255472568\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9976526195074706\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9976914116487187\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9986265621061513\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9986794875430783\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998329031491147\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998213855952455\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.99971964996937\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0000638479446178\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9999930851213428\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000084633698925\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001385898189297\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9999944087203119\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999242589471957\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999597871901419\n",
      "---------> Number of values that have not converged: 2\n",
      "0 5\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9965299529820584\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9990450480043503\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993586513309327\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9998369079306028\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9994251026794031\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995082758994785\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9990961947354494\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999349841355537\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999615655334878\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9999843863734551\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999878640991605\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996477116214741\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998929847182297\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997125089139768\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0000437848179613\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997759262289426\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9998188010738964\n",
      "---------> Number of values that have not converged: 2\n",
      "0 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9999736481461997\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0011774487291518\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0019715481894005\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9999729136346612\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0006769629687737\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9999696566783695\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9999282143464209\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9997026947558664\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994322881246354\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0001358234312867\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997298341853851\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000327546991088\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999693627545827\n",
      "---------> Number of values that have not converged: 2\n",
      "0 7\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9978344963448603\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9988693109385957\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9992028960074558\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9989804001755607\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0000710451342505\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998228986249874\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998684087388598\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999809013109137\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999890907340817\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000688839516576\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999752171693127\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0003497879623249\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000148416346163\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999462567329918\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0002221978412693\n",
      "---------> Number of values that have not converged: 1\n",
      "0 8\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9994374229164538\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9979478067261817\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9990687614705106\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9983855439657412\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9980413124578554\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995876545253889\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993491417439491\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994929095717348\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0001134253341277\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998155033585009\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999820590762738\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998776729227808\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998154223032024\n",
      "---------> Number of values that have not converged: 4\n",
      "0 9\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0097272648867552\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9982818999236205\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9983892711202889\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9991824758134501\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9991863926354854\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9996189283262815\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998593683647883\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003320239496458\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0002783674371303\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997353760722493\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999892528878983\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0004193227878249\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0002616933121062\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0003947297617615\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0001082017887033\n",
      "---------> Number of values that have not converged: 1\n",
      "0 10\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9995760284582803\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0000563894073606\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9994596154623739\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.998466412582672\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9982919478755955\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994907065388782\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996515149965276\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994598741137538\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995223508602015\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996582864229272\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999730937562413\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000911986883552\n",
      "---------> Number of values that have not converged: 1\n",
      "0 11\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0086175574737184\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0007841761558742\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0012381906931018\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.000497728644701\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9993619603791123\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.001022883773122\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0009924680599256\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0010346187197763\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998698010233485\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0001494657545342\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997777126366644\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001104010207167\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995759820664606\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9993891828835205\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997677638456589\n",
      "---------> Number of values that have not converged: 2\n",
      "0 12\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0002682443344626\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000171655516776\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9997620445581307\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0010395963723675\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0004680279090314\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9996633591134102\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.000573546852293\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0002377983622865\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998612457694479\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997767551404997\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996147868721829\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999893009079087\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997847381772642\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998479064489558\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998373660463629\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.000177666846292\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9999337056158689\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9999016429604302\n",
      "---------> Number of values that have not converged: 2\n",
      "0 13\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9986747758721517\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9992108476516606\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0024516438485098\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.001945224885249\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0021876241076815\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0003047479592868\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0011842655076661\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0002424793068116\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0011417645067466\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.001058498616178\n",
      "---------> Number of values that have not converged: 5\n",
      "0 14\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.000734657731187\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0037896146223788\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.002071667725222\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0015260859705444\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0001809501960588\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0005311327566269\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9999982283652408\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999327937544785\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9999207939237923\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995094864272218\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996832978821278\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996491736279646\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0001062982724367\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995773419177238\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997929618080015\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9994764388785256\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997781899230049\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9994663383850161\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9998764739663796\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.999710690134814\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9997206234643902\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9998078934840656\n",
      "---------> Number of values that have not converged: 3\n",
      "0 15\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.003338932552367\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.001834085376109\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000844263391108\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0007872404145657\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.001538099466221\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998824369513829\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003822349958238\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999604480238385\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0001236603949646\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000129376199982\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999765171236506\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000558011701851\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0002381339732063\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000256611767277\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999561018328036\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997769851554601\n",
      "---------> Number of values that have not converged: 3\n",
      "0 16\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9979643254800207\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9997565008827641\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0009975339485393\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0011159341210378\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999408419118608\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0013078382194516\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.00096400988326\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003248407249667\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996610820640361\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998619880343892\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997777357867276\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998463972529267\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997702172772892\n",
      "---------> Number of values that have not converged: 2\n",
      "0 17\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0067602513975953\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0016198515121904\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0012927312971296\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9999465776412123\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0009534857366313\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0010569927895718\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0006765293322135\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0006154393248712\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0014203003155409\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0012339590249586\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003450480580935\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0003055402793801\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000726408989775\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0004688386732978\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0003120374708516\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0002859044011954\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0000148094410197\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0002955581416175\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0003944446837592\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.000522744784574\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0003856395455362\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0004225892612686\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0004341083972044\n",
      "---------> Number of values that have not converged: 3\n",
      "0 18\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9993352526103405\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9994609727252488\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0012383586914924\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9998697055998772\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.000571870259919\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995662481031284\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.99974792469769\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000057181303972\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004745182354413\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000442438864081\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997778925931945\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998284294603788\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996595785533063\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995574039536962\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998653084318011\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.999816511320106\n",
      "---------> Number of values that have not converged: 2\n",
      "0 19\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tianxiao/URDaVa/urdava/urdava/sampling.py:40: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  statistics[i] = (((chain_len - 1) * mean_within_chain_variance + between_chain_variance) /\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "0 20\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0002782058854487\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9994516412717837\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9968527074795969\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9986981143225703\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9997876028521858\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0000216582206363\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0006951561592239\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.99993998847494\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998047397826678\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994708215016127\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0007396724888296\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0003980857669494\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000892941870025\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0005132046878653\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0000868113782717\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0003880967460825\n",
      "---------> Number of values that have not converged: 4\n",
      "1 0\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9933434853195564\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0057820712934646\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.006655310023477\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0024037878029526\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0036913544148067\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0008210716530268\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002893461989208\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.001613090207305\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004248995829854\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998507037358141\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9993951121566781\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997332385846626\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998640324297124\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999027326979791\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998109481535421\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.999966173449884\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997225067081077\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9994653486700464\n",
      "---------> Number of values that have not converged: 3\n",
      "1 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0004296224151519\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0031823533850799\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0041098245354938\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0028132282630469\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9993811610479114\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0020849123071143\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0024349496511669\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0023806134200275\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0017447078663617\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000598367626006\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0017034030620644\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000532732162428\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0005942843183602\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0012258286754108\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0007406407587147\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0031320391819178\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0008871723897435\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0022380118880536\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0007040724204346\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0008825126795884\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0010898871115395\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.000600013625653\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.000917756465496\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.0017114562626153\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.001047091536868\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0003939351592346\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.0005283275218906\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 1.001205707231662\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 1.0009451794354165\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 15000 - Average convergence rate = 1.0007222854000777\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 15500 - Average convergence rate = 1.0003633526881408\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 16000 - Average convergence rate = 1.0005998699405094\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 16500 - Average convergence rate = 1.000379688179078\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 17000 - Average convergence rate = 1.0004441394685808\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 17500 - Average convergence rate = 1.00056470407495\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 18000 - Average convergence rate = 1.0007537607191292\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 18500 - Average convergence rate = 1.0004047773080122\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 19000 - Average convergence rate = 1.0002889775030048\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 19500 - Average convergence rate = 1.0003358781237444\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 20000 - Average convergence rate = 1.000263369688475\n",
      "---------> Number of values that have not converged: 1\n",
      "1 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9918605614216783\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0076116020068282\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0037899627510412\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0021785590031254\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0014622902246206\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000199806124044\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996946770249698\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003351503024696\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995156632834524\n",
      "---------> Number of values that have not converged: 4\n",
      "1 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.000398658701404\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9992017482606527\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9995434512768475\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9989568973764613\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9998410184375978\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998558206652836\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996131297772317\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9988009199156384\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998879643324963\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995183245165435\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997429160931577\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995893933227736\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999481656546544\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997734393763674\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999521566167048\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.999516528256459\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000033275351047\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.999787607135897\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9997823296638072\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0000254391629577\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9998688847676442\n",
      "---------> Number of values that have not converged: 1\n",
      "1 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9989457364882832\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9987650364812871\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.001208194594958\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.99961831262691\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.000118441397963\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9998990843834891\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0001418890979716\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9991964796475922\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0008439571390666\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0004446049801194\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997128032176263\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997242804071301\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0001073249526389\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999891881423591\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999985724314962\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9998507620438195\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997997430952532\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9998426329479444\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.000044079666891\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9999984674086022\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.000027905258779\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.99988667019796\n",
      "---------> Number of values that have not converged: 1\n",
      "1 5\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0025426680144391\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9977002651071808\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9991779906978605\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9990607370002736\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.000921688904232\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994858838124627\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0005368639715344\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0001581289483263\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004596414425098\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0002664169721927\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999956676250772\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000609233624043\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9994373052778673\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000527013791693\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0005877359269129\n",
      "---------> Number of values that have not converged: 3\n",
      "1 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9936751878064398\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9990811728931804\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0010219649722816\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0000937364623184\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0003730739132088\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.00016953897927\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996103961746804\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999095036286098\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0009847271017334\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003497872350644\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003789664985956\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001936602027919\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000311406588769\n",
      "---------> Number of values that have not converged: 3\n",
      "1 7\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0015135897830336\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.004394887375004\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0021013532179468\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9999214558571454\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9994553878110269\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.998819263556962\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.999374205486237\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000011529610018\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0006912727769626\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9989859816852117\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999384323102923\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998911870753883\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9993507977529381\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996618460998198\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998653004750612\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9995967866844627\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000032184511507\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9996967809207568\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.999931087989625\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9996618382974146\n",
      "---------> Number of values that have not converged: 2\n",
      "1 8\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9958887690140902\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9988536918161985\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0038524193483025\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0035480084261728\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0002665639445631\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0022588859410548\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.001642732778379\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9998098092030658\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0009583543637883\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0002180175748292\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0006504578151423\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0003952983093176\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0003378290518017\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999394756942771\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0002832237093167\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0001275469183923\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0002658026699875\n",
      "---------> Number of values that have not converged: 4\n",
      "1 9\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.998318825797676\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9961096504010801\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9985480902967133\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0019304957954795\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0014494721749827\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0006492936487879\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0015672255750314\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003987040257805\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.000765828603229\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0008183910782034\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0009173373705835\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9999611960672355\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0006083963931096\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0002179957407753\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0005835730995825\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0002743266455236\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000298712503769\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0005155139978752\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0004771404623207\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0007300739170912\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0004652777878744\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0003702231318843\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0005055581161335\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000331181097417\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0003420486031545\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0009346753405894\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.000494669526509\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 1.0003230273691222\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 1.0005843966398116\n",
      "---------> Number of values that have not converged: 3\n",
      "1 10\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0109951133683521\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000256043657123\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9960471870858097\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9990683279502283\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0000692015095793\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992591808362633\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.000385314452812\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0001190590959368\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9995044075388555\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000212089043978\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000837948950159\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999670842960929\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000203940428376\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0001700212672187\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998642574125384\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9998456667746386\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9998271531717271\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9997520408590191\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9998975480276958\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9997146996682607\n",
      "---------> Number of values that have not converged: 1\n",
      "1 11\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9982230812296614\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.000492987973954\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.001838806558612\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0006513744475307\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0003010267100032\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994562542996256\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998626583874209\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9991316758874236\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997758540790822\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0001007861215903\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999810124242844\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9993550385864994\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995309998722323\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9998440519812135\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997115707174625\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9995424827929931\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.999894327780841\n",
      "---------> Number of values that have not converged: 1\n",
      "1 12\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9970399533503752\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9973618677514833\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993024139408974\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9992389859906874\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9996508473259329\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994346973372646\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9992466628801249\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9995211696735806\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9991992635032986\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9993044555910489\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997121818562289\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9999342979144982\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9999957349912362\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999093432770317\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0000237494454876\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0001159929952594\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9998226064384458\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.999927613526971\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9998355671816072\n",
      "---------> Number of values that have not converged: 2\n",
      "1 13\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9963644884823385\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9991083787997459\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0002504051226253\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.997358507824574\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9990517451335342\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9992457479603615\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9987824148888643\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992055374160408\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999367148248192\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9993958015480132\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996148404074726\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9994409412709202\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997306529698818\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994971217779415\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9995799591283809\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9993672391751045\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9994273579359018\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995531377319716\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.999681087823617\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9996946804909896\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9994976212491843\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9999223069906898\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9997993432150466\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9996942960934518\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.9997609713237036\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 0.9995627233342553\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 0.9998011082826864\n",
      "---------> Number of values that have not converged: 1\n",
      "1 14\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9965858052408532\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9993181517877797\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9978362004081319\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9976968476011877\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999178763565633\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994589476259231\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998984780141243\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994621786556698\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9998106552843845\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998575422722341\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.000069583247366\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000601288763395\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999841968473164\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0009447430070295\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998897498855834\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0001302790860498\n",
      "---------> Number of values that have not converged: 1\n",
      "1 15\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0112832829371496\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0045999680762714\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0000221299985919\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0009945143607961\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999152535089229\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9985306590489101\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.998529417711469\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9999901991663894\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999256106146067\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995397704117623\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9994318372329132\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9992299777265693\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996727956849519\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994970799977704\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9995838861497554\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999825719063965\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995336015168599\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995079832416937\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9996973749620031\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9998025859799523\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9996144161421584\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9996046226074459\n",
      "---------> Number of values that have not converged: 1\n",
      "1 16\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.996136427013565\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.999634057305169\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0009717251102679\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0003110235609565\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9996967700281113\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9995697012433323\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9986447047180035\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9998274551413657\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994349554728545\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996267206756331\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003555636656891\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001855363067764\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0000477972096729\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999885947373699\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999290532168291\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999871540716687\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0002729354643185\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9999491651511822\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0001207980987112\n",
      "---------> Number of values that have not converged: 1\n",
      "1 17\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0016016702874413\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9979732593490113\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9993481737528874\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0007564823537074\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0010302261472708\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0014145225797602\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9995192106678777\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0011291267657356\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0010110524371396\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.00020876765772\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000498589340272\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000880436115336\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0002630816992821\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0010305729520406\n",
      "---------> Number of values that have not converged: 5\n",
      "1 18\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9971192123787304\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.997630375925529\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9982130971191125\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9985287568304426\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9995153292926587\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9988214785064523\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994508330269607\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9990551336985338\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9991866428032355\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995731946239639\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996289613610357\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997588065042481\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996766218526395\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996091714316125\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9994010323392892\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9995349889574107\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995192766709488\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.999404608401175\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.999454346058819\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9994100058586284\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9994152697529142\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9995185664198791\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9995633999429506\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9996106329842727\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.999612896933855\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 0.9996724530288281\n",
      "---------> Number of values that have not converged: 1\n",
      "1 19\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "1 20\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9953478898970406\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9983390480619709\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9995146813100123\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0003094276650526\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992493544323781\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9989739854519192\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9999594702786374\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0002530750750531\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9992214713005912\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9991603363680014\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.999338352619276\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9993272872574751\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9992182947085415\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994434924141661\n",
      "---------> Number of values that have not converged: 5\n",
      "2 0\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9985427496864969\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9955592289363216\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9986105608348521\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.998803076422521\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9994996697520225\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000153566284964\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996780099866553\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992481702761616\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994123397411078\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9996612268885983\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9994871061528595\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001457223330836\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.99989360041046\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0001677700441418\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9997990729033366\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997389894296367\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9996159199938622\n",
      "---------> Number of values that have not converged: 2\n",
      "2 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.002817705217909\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0005767233598772\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0007909137821867\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0001533236592195\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.999979370659896\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.00018054077608\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9997636037620641\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000162995993738\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0003065110870686\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999715783413583\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997518813673062\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9994716383637309\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998448491059734\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9997707267888606\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996614866514103\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9998201764569531\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9996137460721982\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995760477913316\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.999532726575081\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9994779484145212\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9998418546377383\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9997446258952709\n",
      "---------> Number of values that have not converged: 2\n",
      "2 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.993449294422284\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0007470826169784\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.000053746577641\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.001802831047171\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0002243357938687\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0010288888839434\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0001488199846291\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0003397681107302\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.000425963128612\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9997884709934329\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995641953019959\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998739354775106\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998766597804788\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9996162719494025\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0000017709484974\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0000804146418536\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9996305083580476\n",
      "---------> Number of values that have not converged: 3\n",
      "2 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9997182109344512\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9984856315627196\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9996695820461299\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.000148327675388\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0003120412302675\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9996872553664048\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.000004216944358\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0010093075340294\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9997919005270443\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0000566100237762\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003434661310273\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998320546418094\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999946498924508\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000223645990468\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996826951143202\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9996570695477448\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0001508021405174\n",
      "---------> Number of values that have not converged: 2\n",
      "2 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0130610990137179\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0020943227727694\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0005016346602404\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9999956001695751\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9988834760571975\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9990433430780373\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9996131700169345\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9990424163740155\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994090368582186\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9993853512602744\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9992819665928074\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997626687050234\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9995859017672837\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9994945428327382\n",
      "---------> Number of values that have not converged: 3\n",
      "2 5\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9980110528617385\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9967524819070767\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9992530966071477\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9998027254811688\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9993891618300893\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991663727493543\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9997954912734622\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.999437974905076\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9999465998963458\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9992992651655972\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9992847633732809\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996202057471494\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996748462844346\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995886285080386\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9994313006562717\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9995752539003774\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995114857145883\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9997097166043325\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9994807657887602\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9997807135852886\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9996159547609018\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9999665394627474\n",
      "---------> Number of values that have not converged: 2\n",
      "2 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.00263781342261\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0008251094312104\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0004610493114277\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0005485726557704\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0006647560700939\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000777595216414\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0004544346307622\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.000198367748686\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004272971436257\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003320508137021\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0003684729029774\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.000172809317825\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998658447520136\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0002596466172706\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999570295722796\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0004484456114715\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997148770796916\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9996948752006057\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0001244493562338\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0000190814441063\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.00029334115151\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.000127638323162\n",
      "---------> Number of values that have not converged: 1\n",
      "2 7\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9953762035035464\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9956774997853802\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9976373660971216\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.000439913412464\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9991822160912727\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9994534078074923\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9995552016986892\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0006499801844855\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994169003152504\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9995299904542225\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0001978964580773\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.999298619204962\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.999819651002326\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999649926921831\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998307718253212\n",
      "---------> Number of values that have not converged: 4\n",
      "2 8\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0050627752967323\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.001729487974113\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0066020327223868\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0026773979139703\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0039429762330558\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0007450121661166\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9998690589305527\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0012397613391542\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0006922693916416\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.000593640790974\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998120411787306\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9996980366416048\n",
      "---------> Number of values that have not converged: 2\n",
      "2 9\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9973891517217415\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0001312282173627\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0016821724965703\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0010717658413457\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9999287029090719\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9999425251177826\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994109298397494\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9993070587907259\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9989971638264281\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994459341928136\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9995950534048966\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995992904748482\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9993653543750218\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999370103334409\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9992796585833457\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9993366311787529\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9995717237759943\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9994342264638925\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9995908030368232\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.9995186236191277\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9997153036187547\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.999639027163869\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 0.9996995866881847\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9996992453409819\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.999682577725951\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 0.999550416667974\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 0.9996604624914829\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 0.9995965521260342\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 0.9996520082419112\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 15000 - Average convergence rate = 0.9996056181990293\n",
      "---------> Number of values that have not converged: 2\n",
      "2 10\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0004997297288913\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0014392608787028\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9981851719953543\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9996147809341717\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9989683350633168\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9993735661450188\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9992796477899738\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992384063702219\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996600162719665\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9998174832762164\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9999559759182546\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.99941420109518\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998494956091902\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0004756115220879\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.0001491410072243\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0001688928079684\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0001957437664994\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0001892562295447\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0005034928818402\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0001342046212167\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9998521986401059\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0003881260746006\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0000953205122805\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.0000939314168802\n",
      "---------> Number of values that have not converged: 2\n",
      "2 11\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9962519819857162\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9982372151069141\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.998451501882481\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9973545661804702\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9988843967615969\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9988148013592671\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9994952542078569\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9991053119796325\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9994468591685975\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994725143746709\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9997988190915406\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9998292863276088\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9997322967721818\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.999947469588553\n",
      "---------> Number of values that have not converged: 1\n",
      "2 12\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9974390334571552\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9985928064640158\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 1.0010327601970415\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0020458321488552\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0016991941270652\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0009146783331833\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003303597046187\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0002646517716056\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0003993546856282\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999885485256129\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000113977516811\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997260738720565\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.000816637604253\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0001590946750982\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.999813731899405\n",
      "---------> Number of values that have not converged: 1\n",
      "2 13\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9958426281358396\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9983434957317027\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9998976442235766\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0007253678335148\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0000500781238317\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9996250115841837\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9993636988758671\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.0004239797633259\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999967478793427\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0002000607025654\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9998844752237089\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9995833176584403\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9994737034864061\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0000541816796782\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9998904759003907\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997056963165587\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.999678305287353\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9998410669121179\n",
      "---------> Number of values that have not converged: 1\n",
      "2 14\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0012124681606727\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.0007228559145802\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9996555173950573\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0000017884959622\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0001186206920771\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0005308638560126\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0003485819505011\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994712181413062\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0004425711960758\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0003429059973235\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0001537277093562\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000322219155742\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0004486197755407\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0009797504027587\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000609843928202\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0001136287689254\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.0003982187901383\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0010357530102136\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0006758282379167\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0005951355247185\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0005334669588295\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.000121304304058\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0006353771980783\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.0004335471298995\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.9999338949580235\n",
      "---------> Number of values that have not converged: 1\n",
      "2 15\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0039364868680523\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 1.001505850063675\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9981789702177712\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.999448120134882\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9992833740809317\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.000522266330892\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0002707135233313\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9996369898051917\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.999999390807958\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0001388429260682\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0000256178855558\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0000237756946782\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9998922456669616\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9999300299949594\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9999397292303761\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999354337625778\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9997293051426178\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.000178228007383\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0003295558306606\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0000094196725426\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0000238579566616\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 0.9999535136002567\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.0002195131674776\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 0.9999074049271308\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 0.9998818316273222\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0000605931629816\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.0001403268909332\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 14000 - Average convergence rate = 0.9998165369327117\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 14500 - Average convergence rate = 0.9998702036462253\n",
      "---------> Number of values that have not converged: 1\n",
      "2 16\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0011038561027632\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9975574537142279\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9986548110243074\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 1.0017867078643745\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 1.0008244453979236\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 1.0014864786331885\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 1.0007710862877401\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 1.001064702271937\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 1.0000824465038105\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 1.0008579092344296\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.0001739791164277\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 1.0001221731287282\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 1.0006674848093213\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.0010603230699646\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 1.000202149303609\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 1.0002569029350725\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 1.000122905656135\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 1.0000700469476087\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 1.0001485350662729\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 1.0001697683832158\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 1.0002781581422782\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 11000 - Average convergence rate = 1.0003328743718785\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 11500 - Average convergence rate = 1.000377049785656\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12000 - Average convergence rate = 1.000450772281688\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 12500 - Average convergence rate = 1.0003222281004083\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 13000 - Average convergence rate = 1.0003568980012503\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 13500 - Average convergence rate = 1.0001195045091418\n",
      "---------> Number of values that have not converged: 1\n",
      "2 17\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 0.9974970398381563\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9962080611872907\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9983188098304924\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9981576526114605\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9993030615673218\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9991270387443766\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9999265667821639\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9994257033349606\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9996166843904325\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.999736038268991\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 1.000115784948556\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9999228942253177\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9996135874147066\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 1.000075251050765\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9996508410363952\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9999461992028378\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9996486963220814\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.9995481059173202\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.9994451891003554\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 10000 - Average convergence rate = 0.999852936684956\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 10500 - Average convergence rate = 0.9996081604881057\n",
      "---------> Number of values that have not converged: 1\n",
      "2 18\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = 1.0008577079054655\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = 0.9989640013658141\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = 0.9982233778541203\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = 0.9977782942982393\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = 0.9991403972385928\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = 0.9990661029223872\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = 0.9988912360037773\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = 0.9992789678221272\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = 0.9999247397951719\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = 0.9994502610053818\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = 0.9996719208097223\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = 0.9997122786591496\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = 0.9994435414680135\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = 0.9995129355145362\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = 0.9993890747763352\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = 0.9997033064065279\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 8500 - Average convergence rate = 0.9994161666636373\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 9000 - Average convergence rate = 0.99951851372425\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 9500 - Average convergence rate = 0.99981234930153\n",
      "---------> Number of values that have not converged: 2\n",
      "2 19\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 5\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 4\n",
      "====> Monte-Carlo Round 5000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 5500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 6000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 6500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "====> Monte-Carlo Round 7000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 7500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 3\n",
      "====> Monte-Carlo Round 8000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 2\n",
      "2 20\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 0\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 1\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 2\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 3\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 4\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 5\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 1500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 2500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 3500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "====> Monte-Carlo Round 4000 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 7\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 8\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 9\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 10\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 11\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 12\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 13\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 14\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 500 - Average convergence rate = nan\n",
      "---------> Number of values that have not converged: 1\n",
      "3 15\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 16\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 17\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 18\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 19\n",
      "====> Monte-Carlo Round 0 - Average convergence rate = 0.0\n",
      "---------> Number of values that have not converged: 6\n",
      "3 20\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from derdava.dataset import load_dataset\n",
    "from derdava.data_source import generate_random_data_sources\n",
    "\n",
    "X, y = load_dataset('phoneme')\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, shuffle=True)\n",
    "data_sources = generate_random_data_sources(X_train, y_train)\n",
    "\n",
    "data_sources[5] = (data_sources[0][0].copy(), data_sources[0][1].copy()) # 5 is a duplicate of 0\n",
    "\n",
    "from urdava.data_valuation import ValuableModel\n",
    "from urdava.model_utility import IClassificationModel, model_logistic_regression\n",
    "\n",
    "model_utility_function = IClassificationModel(model_logistic_regression, data_sources, X_test, y_test)\n",
    "\n",
    "valuable_model = ValuableModel(tuple([i for i in range(6)]), model_utility_function)\n",
    "\n",
    "from urdava.coalition_probability import IndependentCoalitionProbability\n",
    "\n",
    "x = [[] for i in range(4)]\n",
    "y = [[] for i in range(4)]\n",
    "\n",
    "for i in range(4): # 100%, 67%, 33%, 0%:\n",
    "    x[i] = [1 - 0.05 * j for j in range(21)]\n",
    "    for j in range(21): # 100%, 90%, ..., 10%, 0%\n",
    "        coalition_probability = IndependentCoalitionProbability({0: 1 - 0.05 * j, 1: 1 - 1/3 * i, \n",
    "                                                                 2: 1 - 1/3 * i, 3: 1 - 1/3 * i,\n",
    "                                                                 4: 1 - 1/3 * i, 5: 1 - 1/3 * i}) \n",
    "        to_be_appended = valuable_model.valuate(data_valuation_function='012-mcmc robust shapley', \n",
    "                                                coalition_probability=coalition_probability, tolerance=1.0005)[0]\n",
    "        while to_be_appended < 0.001 and j != 20:\n",
    "            to_be_appended = valuable_model.valuate(data_valuation_function='012-mcmc robust shapley', \n",
    "                                                coalition_probability=coalition_probability, tolerance=1.0005)[0]\n",
    "        y[i].append(to_be_appended)\n",
    "        \n",
    "shapley_score = valuable_model.valuate(data_valuation_function='shapley')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "df66d82b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x[0], [shapley_score] * 21, linestyle='dashed', color='gray', label='Shapley')\n",
    "for i in range(4):\n",
    "    ax.plot(x[i], y[i], color='C' + str(i), label=f'{round((1 - 1/3 * i)*100)}% stay')\n",
    "    \n",
    "ax.set_xlabel(r'Staying prob of $\\mathtt{DUP}$', fontsize=30)\n",
    "ax.set_ylabel('Valuation score', fontsize=30)\n",
    "ax.legend(facecolor='white', framealpha=1, fontsize='xx-large', loc='upper right')\n",
    "ax.tick_params(axis='both', labelsize='xx-large')\n",
    "plt.gca().invert_xaxis()\n",
    "PATH_TO_IMAGES = \"./images/data_similarity/\"\n",
    "if not os.path.isdir(PATH_TO_IMAGES):\n",
    "    os.makedirs(PATH_TO_IMAGES)\n",
    "fig.savefig(os.path.join(PATH_TO_IMAGES, \"ds_5_phoneme_lr_shapley\"), dpi=300, bbox_inches='tight')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}